Add MapReduceWorkload scaffold and generic workload execution

.opencode/session-goal.md

@@ -0,0 +1,26 @@
+COMPLETED
+# Session Goal
+
+адаптируй код под sdk, где это необходимо. при надобности доработай SDK. главное чтобы workloads можно было дописывать не трогая остальной код программы, так как он в будущем будет закрытым. Workloads - в первую очередь пользовательские скрипты, поэтому sdk должен полностью покрывать необходимый функционал.
+
+## Plan
+
+1. SDK: добавить высокоуровневый каркас MapReduceWorkload (scimesh/sdk/batch.py) — манифест/стейджи/definition собираются автоматически, планировщик/раннер/редуктор — общий скелет с хуками (partition_input, compute_shard, parse/validate_partial_keys, reduce_partials, domain_validate).
+2. Рефакторинг: descriptor-batch, similarity-search, similarity-graph переписать на базовый класс (поведение/байты не меняются — парность покрыта тестами).
+3. Worker (закрываемый код): обобщить SciMeshRunner — загрузка ворклоадов из конфига/дискавери (allowlist), инвентарь из конфига воркера, fail-closed для неподдерживаемых форм; конфиг: SCIMESH_CAPABILITIES, SCIMESH_WORKLOAD_ALLOWLIST.
+4. CLI: добавить общий `scimesh workload list|run` (generic SDK-инструмент, без workload-специфичной логики) — пользовательские скрипты можно запускать локально без правки остального кода.
+5. Тесты: test_sdk_batch.py (каркас + хуки + fail-closed), тесты воркера на не-search ворклоаде, CLI-тесты; регрессия парности.
+6. Документация: workload-sdk.md (авторский гайд на базе MapReduceWorkload), handoff, STATUS.
+7. Полный прогон pytest, финальная верификация.
+
+## Progress
+
+- [x] `scimesh/sdk/batch.py`: `MapReduceWorkload` — identity/parameters/ports + 3 научных хука; сборка манифеста, map/reduce стейджей, workflow, pinned handlers, exact-artifact verifier; хуки: domain_validate, resolved_parameters, resolved_parameters_for_plan, plan_tasks, parse/validate_partial_keys, map_stage_inputs; экспортирован из scimesh.sdk.
+- [x] descriptor-batch, similarity-search, similarity-graph переписаны на MapReduceWorkload; парность с локальными reference сохранена (тесты byte-identical зелёные). `query_id`-резолюция переехала в run_search_shard (ворклоад сам валидирует параметры).
+- [x] Worker обобщён: SciMeshRunner принимает definitions+inventory+runtime, `for_worker(config)` грузит ворклоады через allowlist-дискавери (entry points) или built-in fallback; fail-closed для map-стейджей не по v1-контракту (single input); параметры таски проходят насквозь, валидация в ворклоаде. Конфиг: SCIMESH_CAPABILITIES, SCIMESH_WORKLOAD_ALLOWLIST (JSON {distribution,name,version,digest}); парсер вынесен в SDK (`workload_allowlist_from_json`).
+- [x] CLI: `scimesh workload list|run` (generic; SCIMESH_WORKLOAD_ALLOWLIST поддерживается; runtime строится из discovered-ворклоадов); зарегистрирован как ворклоад-модуль.
+- [x] `default_sdk_registry(allowlist=...)` и `default_sdk_runtime(workload_capabilities=..., environment_digests=...)` в library.
+- [x] Тесты: test_sdk_batch.py (5), test_cli_workload.py (6, включая end-to-end allowlisted custom workload), worker: generic execution (descriptor-batch), v1-contract rejection (graph), for_worker discovery, config parsing.
+- [x] Документация: workload-sdk.md (раздел "Authoring a workload" + worker/CLI), handoff, STATUS, README.
+- [x] Финальная верификация: 249 passed; scimesh workload list/run работают; scimesh.sdk не импортирует workloads (grep чист).
+- Изменения НЕ закоммичены (по AGENTS.md коммит только по явной просьбе).

README.md

@@ -145,7 +145,9 @@ workload code. Workloads are user scripts built on the SDK: the built-in
 composed by `scimesh/workloads/library.py` and registered through
 `scimesh.workloads` entry points. The Worker Agent executes those SDK-built
 workloads directly (see `scimesh/worker/runners.py`), so the same scientific
-handlers run locally, in conformance, and on claimed coordinator tasks. See the
+handlers run locally, in conformance, and on claimed coordinator tasks.
+`scimesh workload list` and `scimesh workload run` run any SDK workload from
+the command line. See the
 [SDK author guide](docs/workload-sdk.md), [contract](docs/scimesh-sdk-contract.md),
 and [delivery roadmap](docs/scimesh-sdk-roadmap.md).
 

STATUS.md

@@ -51,7 +51,8 @@ the complete result-artifact SHA-256 before a task is accepted.
 | CTX-15 User Service and access control | Implemented | User/owner scoping, verified contributors, worker keys, self-service enrollment, and quorum-backed untrusted workers are merged; local Go/Python and Docker/PostgreSQL checks passed. |
 | CTX-16 Workload SDK foundation | Implemented | `scimesh.sdk` provides strict immutable manifests/plans/artifacts, digest/trust-pinned tasks, typed DAGs, compatibility negotiation, verifier primitives with owner/binding-safe quorum inputs, resource eligibility/local allocation, measured package discovery, a trusted local core-batch conformance harness, and strict package discovery. Enforcing coordinator/Worker profiles remain fail-closed. |
 | SDK roadmap step 3: `descriptor-batch` | Implemented | The first SDK-built reference workload (`scimesh/workloads/descriptors/`): pinned 81-name RDKit 2D descriptor set, canonical one-row-per-input CSV, deterministic row-bounded shards, shard-index concatenation with one header, byte-identical local/distributed output, and a two-worker `untrusted_quorum` verifier test. |
-| SDK-built `similarity-search` and `similarity-graph` | Implemented | Both workloads are now SDK-built packages (`scimesh/workloads/search/`, `scimesh/workloads/graph/`) with their own manifests/planners/runners/reducers on the `core-batch-v1` profile; they reuse the local scientific cores and are byte-identical to the single-process references (search; graph for both threshold directions and any block size). The graph reducer enforces the CTX-10 pair-coverage invariant. `scimesh/workloads/library.py` composes the built-in registry/runtime. |
+| SDK-built `similarity-search` and `similarity-graph` | Implemented | Both workloads are SDK-built packages (`scimesh/workloads/search/`, `scimesh/workloads/graph/`) built on the `MapReduceWorkload` authoring scaffold (`scimesh/sdk/batch.py`); they reuse the local scientific cores and are byte-identical to the single-process references (search; graph for both threshold directions and any block size). The graph reducer enforces the CTX-10 pair-coverage invariant. `scimesh/workloads/library.py` composes the built-in registry/runtime. |
+| SDK authoring scaffold | Implemented | `MapReduceWorkload` (exported from `scimesh.sdk`) assembles manifest, map/reduce stages, workflow, and digest-pinned handlers from three scientific hooks (partition/compute/merge), with overridable hooks for domain validation, plan-time resolution, custom task planning, and partial-key policy. The generic `scimesh workload list|run` CLI and the worker's allowlist-driven loading (`SCIMESH_WORKLOAD_ALLOWLIST`, `SCIMESH_CAPABILITIES`) let new workloads run without touching other code. |
 
 ## Next recommended assignment
 
@@ -63,9 +64,10 @@ block-pair planning and reduction for `similarity-graph`.
 - The worker/coordinator flow accepts both underscore API workload names and
   hyphenated names at the runner boundary; the runner normalizes them.
 - The worker executes SDK-built workloads through `scimesh/worker/runners.py`
-  (a v1-wire bridge over `TaskSpec`/`LocalTaskContext`); the CTX-07
+  (a workload-generic v1-wire bridge over `TaskSpec`/`LocalTaskContext`);
-  `DistributedWorkload` protocol module and the SDK compatibility adapter were
+  `query_id` resolution and parameter validation live in the workload itself.
-  removed. `max_rows` is a plan-time option and is rejected per task.
+  `max_rows` is a plan-time option and is rejected per task by the stage
+  projection.
 - A real-stack worker test uses a small `query_smiles` shard. The Python
   planner resolves `query_id` once and shares `query_smiles`; the upload UI
   currently accepts `query_smiles` only.

docs/sdk-handoff.md

@@ -24,6 +24,24 @@ partial writer moved to `scimesh/workloads/search/core.py`; the partial
 format is unchanged, so the Go reducer and UI keep working. The runner
 resolves `query_id` per task and rejects plan-time `max_rows`.
 
+**Authoring scaffold (2026-08-01):** `scimesh/sdk/batch.py` adds
+`MapReduceWorkload` — the primary authoring surface for `core-batch-v1`. A
+subclass declares identity/parameters/ports and three scientific hooks
+(`partition_input`, `compute_shard`, `reduce_partials`); the SDK assembles the
+manifest, map/reduce stages, workflow, digest-pinned handlers, and the
+exact-artifact verifier. Overridable hooks: `domain_validate`,
+`resolved_parameters`, `resolved_parameters_for_plan`, `plan_tasks`,
+`parse_partial_key`/`validate_partial_keys`, `map_stage_inputs` (multi-input
+map stages share the external input schema). All three built-in workloads are
+refactored onto it. Generic `scimesh workload list|run` CLI added (no
+workload-specific logic). The worker loads workloads generically:
+`SCIMESH_WORKLOAD_ALLOWLIST` (JSON `{distribution, name, version, digest}`,
+discovery via entry points) or built-in fallback; `SCIMESH_CAPABILITIES`
+overrides advertised capabilities; workloads with multi-input map stages are
+rejected by the v1 bridge. `query_id` resolution moved into the search
+workload's `run_search_shard`; the worker passes task parameters through and
+the workload validates them.
+
 CTX-16 "Workload SDK foundation" is complete and tested. `scimesh/sdk/`
 implements the `core-batch-v1` profile:
 

docs/workload-sdk.md

@@ -55,7 +55,12 @@ The stable authoring surface is exported from `scimesh.sdk`:
   protocols;
 - `OutputManifest` and `Provenance` describe sealed durable results;
 - `WorkloadRegistry` resolves an exact name, version, package digest, runtime,
-  environment, and feature set. It never selects an implicit latest version.
+  environment, and feature set. It never selects an implicit latest version;
+- `MapReduceWorkload` is the primary authoring scaffold for `core-batch-v1`:
+  a subclass declares its identity, parameter schema, artifact ports, and
+  three scientific hooks (partition, compute, merge), and the SDK assembles
+  the manifest, map/reduce stages, workflow, digest-pinned handlers, and the
+  exact-artifact verifier. See "Authoring a workload" below.
 
 Persisted manifests, requests, plans, tasks, expansions, outputs, candidates,
 decisions, and failures are frozen, recursively immutable, JSON-safe,
@@ -202,11 +207,126 @@ the local scientific cores from `scimesh/workloads/similarity_search.py` and
   compared exactly once, no duplicates) before emitting the same
   deterministically sorted edge list as the local brute-force reference, for
   either threshold direction and any block size;
-- the v1 worker executes the SDK-built `similarity-search` runner directly:
+- the v1 worker executes SDK-built workloads directly:
-  `scimesh/worker/runners.py` is a small wire bridge that builds a `TaskSpec`
+  `scimesh/worker/runners.py` is a workload-generic wire bridge that builds a
-  with the workload's own pins, reserves resources, seals the partial through
+  `TaskSpec` with the workload's own pins, negotiates against a runtime
-  a content-addressed store, and uploads the resulting CSV over the unchanged
+  derived from the loaded definitions, reserves resources, seals the partial
-  coordinator contract.
+  through a content-addressed store, and uploads the resulting CSV over the
+  unchanged coordinator contract. The worker loads workloads from
+  `SCIMESH_WORKLOAD_ALLOWLIST` (a JSON array of
+  `{distribution, name, version, digest}` entries matched against installed
+  `scimesh.workloads` entry points) or falls back to the built-in
+  `similarity-search`; advertised capabilities come from
+  `SCIMESH_CAPABILITIES`. Workloads whose map stage needs more than one input
+  port are rejected with a clear message until the coordinator contract
+  supports them.
+
+## Authoring a workload
+
+A workload is a user script that imports the SDK. For the standard
+`core-batch-v1` shape (one input dataset, shards, partials, one merged result)
+subclass `MapReduceWorkload` and implement the three scientific hooks; the
+framework provides everything else:
+
+```python
+from pathlib import Path
+from typing import Any, Mapping, Sequence
+
+from scimesh.sdk import (
+    ArtifactSchema,
+    ComponentRef,
+    MapReduceWorkload,
+    PortSpec,
+    SchemaRef,
+    WorkloadId,
+)
+
+class CountRowsWorkload(MapReduceWorkload):
+    workload_id = WorkloadId("count-rows", "1.0.0")
+    description = "Count TSV data rows per shard and concatenate the counts."
+    parameters_schema = {
+        "type": "object",
+        "additionalProperties": False,
+        "properties": {"prefix": {"type": "string", "minLength": 1, "maxLength": 50}},
+    }
+    input_port = PortSpec(ArtifactSchema(
+        SchemaRef("molecule-table", 1), "text/tab-separated-values", "utf-8",
+        max_bytes=10**9, validator=ComponentRef("delimited-table", 1),
+        validator_configuration={"required_columns": ["canonical_smiles", "chembl_id"]},
+    ))
+    partial_port = output_port = PortSpec(ArtifactSchema(
+        SchemaRef("count-table", 1), "text/csv", "utf-8",
+        max_bytes=10**9, validator=ComponentRef("delimited-table", 1),
+        validator_configuration={"columns": ["id", "rows"]},
+    ))
+    map_parameter_names = ("prefix",)
+
+    def partition_input(self, input_path, parameters, workspace):  # -> list[Path]
+        ...  # deterministic shard files, one per map task
+
+    def compute_shard(self, inputs, parameters, output_path):  # -> Mapping[str, int|float]
+        ...  # one map task; inputs maps each map port to a materialized file
+
+    def reduce_partials(self, partial_paths, parameters, output_path):  # -> Mapping[str, int|float]
+        ...  # deterministic merge of the accepted partials
+```
+
+The base class then provides `validate`, `plan`, `run`, `reduce`, and
+`definition()`; the registry, negotiation, resource reservation, verification,
+and the local conformance executor treat the result like any other workload:
+
+```python
+from scimesh.sdk import (
+    ArtifactCollection,
+    JobRequest,
+    LocalArtifactStore,
+    LocalCoreBatchExecutor,
+    WorkloadRegistry,
+)
+from scimesh.workloads.library import default_sdk_runtime
+
+workload = CountRowsWorkload(package_digest=..., environment_digest=...)
+registry = WorkloadRegistry()
+registry.register(workload.definition(), enabled=True)
+
+store = LocalArtifactStore(Path("artifacts"))
+artifact = store.import_file(Path("tiny.tsv"), declaration=workload.manifest.inputs["input"].schema)
+request = JobRequest(workload=workload.manifest.workload, parameters={"prefix": "x"},
+                     inputs={"input": ArtifactCollection.single(artifact)})
+result = LocalCoreBatchExecutor(registry, default_sdk_runtime(), store, Path("work")) \
+    .execute(request, workload.manifest.package.digest)
+```
+
+Hooks you can override beyond the three scientific ones:
+
+- `domain_validate(parameters)` — extra job-parameter validation (the JSON
+  schema already ran);
+- `resolved_parameters(request)` / `resolved_parameters_for_plan(job, input_path, resolved)`
+  — values persisted into the plan (for example one-time query resolution);
+- `plan_tasks(...)` — custom task construction (the graph workload uses this
+  to plan one task per block pair with two block inputs);
+- `parse_partial_key(key)` / `validate_partial_keys(parsed)` — partial-key
+  policy (default: `map.<eight-digit-index>`, contiguous; the graph workload
+  parses `map.<i>x<j>` and enforces the pair-coverage invariant);
+- `map_stage_inputs` — a map stage with more than one input port (each extra
+  port must share the external input schema).
+
+Anything outside this model uses the lower-level SDK value objects directly.
+Authoring rules: keep the scientific core callable without a coordinator,
+inline a strict JSON parameter schema, declare artifact schemas with bounds,
+return only sink-sealed artifacts, and select a verifier compatible with
+determinism and trust.
+
+To run a workload from the command line without writing any program code:
+
+```bash
+scimesh workload list
+scimesh workload run count-rows --input tiny.tsv --params '{"prefix": "x"}' -o result.csv
+```
+
+`scimesh workload` is a generic SDK tool; it contains no workload-specific
+logic, so new workloads do not require changes to the CLI or any other part of
+the program.
 
 ## Package shape and registration
 

scimesh/sdk/__init__.py

@@ -19,6 +19,7 @@ from .artifacts import (
     PortSpec,
     Provenance,
 )
+from .batch import MapReduceWorkload
 from .conformance import (
     CancellationFlag,
     LocalArtifactStore,
@@ -77,6 +78,7 @@ from .registry import (
     WorkloadDefinition,
     WorkloadDescription,
     WorkloadRegistry,
+    workload_allowlist_from_json,
 )
 from .resources import (
     AcceleratorDevice,
@@ -155,6 +157,7 @@ __all__ = [
     "LocalTaskContext",
     "LoopSpec",
     "MANIFEST_SCHEMA_VERSION",
+    "MapReduceWorkload",
     "NegotiatedWorkload",
     "NetworkPolicy",
     "NumericTolerance",
@@ -207,6 +210,7 @@ __all__ = [
     "WorkloadLimits",
     "WorkloadManifest",
     "WorkloadRegistry",
+    "workload_allowlist_from_json",
     "assert_manifest_round_trip",
     "installed_distribution_digest",
     "negotiate_manifest",

scimesh/sdk/batch.py

@@ -0,0 +1,554 @@
+"""High-level core-batch-v1 authoring scaffold for map/reduce workloads.
+
+``MapReduceWorkload`` is the SDK's primary authoring surface for the
+``core-batch-v1`` profile: a subclass declares its identity, parameter
+schema, artifact ports, and three scientific hooks (partitioning, per-shard
+computation, partial merging), and the base class assembles the immutable
+manifest, the map/reduce stages, the workflow DAG, the digest-pinned
+planner/runner/reducer handlers, and the exact-artifact verifier.
+
+The base class deliberately supports only the static byte-exact map/reduce
+shape with a single external input and one output port. Workloads that need
+a different DAG (for example block-pair tasks with two map inputs) override
+the ``map_stage_inputs``, ``plan_tasks``, ``parse_partial_key``, and
+``validate_partial_keys`` hooks; anything outside the model must use the
+lower-level SDK value objects directly.
+"""
+
+from __future__ import annotations
+
+import hashlib
+import shutil
+from pathlib import Path
+from typing import Any, Mapping, Sequence
+
+from .artifacts import (
+    ArtifactCollection,
+    ArtifactItem,
+    ArtifactRef,
+    ArtifactSchema,
+    Cardinality,
+    CollectionKind,
+    OutputManifest,
+    PortSpec,
+)
+from .execution import (
+    CheckpointPolicy,
+    ExecutionProfile,
+    NetworkPolicy,
+    RetryPolicy,
+)
+from .identity import ComponentRef, VersionRange, WorkloadId
+from .manifest import (
+    DeterminismProfile,
+    EnvironmentSpec,
+    PackageSpec,
+    TrustMode,
+    VerifierSpec,
+    WorkloadLimits,
+    WorkloadManifest,
+)
+from .plans import JobRequest, TaskSpec, ValidatedJob, WorkflowPlan
+from .protocols import PlanningContext, ReduceContext, TaskContext
+from .registry import WorkloadDefinition
+from .resources import ResourceRequirements
+from .verification import ExactArtifactVerifier
+from .workflow import ArtifactEdge, PortRef, StageKind, StageSpec, WorkflowSpec
+
+_EXACT_ARTIFACT = ComponentRef("exact-artifact", 1)
+_EXACT_VERIFIER = ExactArtifactVerifier()
+
+
+def _sha256_file(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as source:
+        for block in iter(lambda: source.read(1024 * 1024), b""):
+            digest.update(block)
+    return digest.hexdigest()
+
+
+def _default_entry_point(module: str, kind: str) -> str:
+    return f"{module}:{kind}@v1"
+
+
+class MapReduceWorkload:
+    """Base class for static byte-exact map/reduce workloads.
+
+    Required class attributes:
+
+    - ``workload_id``: ``WorkloadId`` identity (name + version);
+    - ``parameters_schema``: strict JSON object schema (the registry validates
+      ``additionalProperties: false`` for the top level);
+    - ``input_port``, ``partial_port``, ``output_port``: typed ``PortSpec``
+      values for the external input, one map partial, and the final result.
+
+    Scientific hooks (override as needed):
+
+    - ``domain_validate(parameters)``: extra job-parameter validation;
+    - ``resolved_parameters(request)``: values carried into the plan;
+    - ``partition_input(input_path, parameters, workspace)``: deterministic
+      shard splitting; returns one TSV/CSV file per map task;
+    - ``plan_tasks(shard_paths, resolved, job, negotiated, map_stage, context)``:
+      task construction (default: one task per shard, ``map/<index>``);
+    - ``compute_shard(inputs, parameters, output_path)``: one map task;
+      ``inputs`` maps every ``map_stage_inputs`` port to a materialized file;
+    - ``parse_partial_key(key)`` and ``validate_partial_keys(parsed)``:
+      partial-key policy for the reducer;
+    - ``reduce_partials(partial_paths, parameters, output_path)``: the
+      deterministic merge.
+
+    Optional class attributes: ``map_stage_inputs`` (default one ``input``
+    port), ``map_parameter_names``, ``reduce_parameter_names``, ``capabilities``,
+    ``trust_modes``, ``workflow_id``, ``limits``, ``resources``, ``execution``,
+    ``map_entry_point``, ``reduce_entry_point``.
+    """
+
+    workload_id: WorkloadId
+    description: str = ""
+    parameters_schema: Mapping[str, Any] = {}
+    input_port: PortSpec
+    partial_port: PortSpec
+    output_port: PortSpec
+
+    map_stage_inputs: Mapping[str, PortSpec] | None = None
+    map_parameter_names: tuple[str, ...] = ()
+    reduce_parameter_names: tuple[str, ...] = ()
+    capabilities: tuple[str, ...] | None = None
+    trust_modes: tuple[TrustMode, ...] = (TrustMode.TRUSTED, TrustMode.UNTRUSTED_QUORUM)
+    workflow_id: str | None = None
+    limits: WorkloadLimits | None = None
+    resources: ResourceRequirements | None = None
+    execution: ExecutionProfile | None = None
+    map_entry_point: str | None = None
+    reduce_entry_point: str | None = None
+
+    def __init__(
+        self,
+        *,
+        package_digest: str,
+        environment_digest: str,
+    ) -> None:
+        workload_id = self.workload_id
+        if not isinstance(workload_id, WorkloadId):
+            raise ValueError("workload_id must be a WorkloadId")
+        if not isinstance(self.input_port, PortSpec):
+            raise ValueError("input_port must be a PortSpec")
+        if not isinstance(self.partial_port, PortSpec):
+            raise ValueError("partial_port must be a PortSpec")
+        if not isinstance(self.output_port, PortSpec):
+            raise ValueError("output_port must be a PortSpec")
+        if not self.parameters_schema:
+            raise ValueError("parameters_schema must be provided")
+        module = type(self).__module__
+        self.map_entry_point = self.map_entry_point or _default_entry_point(
+            module, "map"
+        )
+        self.reduce_entry_point = self.reduce_entry_point or _default_entry_point(
+            module, "reduce"
+        )
+        self.entry_point = self.map_entry_point
+        self.map_stage_inputs = dict(
+            self.map_stage_inputs or {"input": self.input_port}
+        )
+        if set(self.map_stage_inputs) != {"input"} and any(
+            port.schema != self.input_port.schema
+            for port in self.map_stage_inputs.values()
+        ):
+            raise ValueError(
+                "additional map inputs must share the external input schema"
+            )
+        self.map_parameter_names = tuple(self.map_parameter_names)
+        self.reduce_parameter_names = tuple(
+            self.reduce_parameter_names or self.map_parameter_names
+        )
+        self.capabilities = tuple(self.capabilities or (workload_id.name,))
+        if workload_id.name not in self.capabilities:
+            raise ValueError("capabilities must include the workload name")
+        name = workload_id.name
+        resources = self.resources or ResourceRequirements(
+            profile=f"{name}-cpu-v1",
+            cpu_cores=1,
+            memory_mb=1024,
+            scratch_mb=1024,
+            max_duration_seconds=3600,
+        )
+        execution = self.execution or ExecutionProfile(
+            profile=f"{name}-python-process-v1",
+            network=NetworkPolicy.TRUSTED,
+            timeout_seconds=3600,
+            checkpoint=CheckpointPolicy(),
+        )
+        limits = self.limits or WorkloadLimits(
+            max_input_bytes=self.input_port.schema.max_bytes,
+            max_tasks=10_000,
+            max_output_bytes=self.output_port.schema.max_bytes,
+        )
+        trust_values = tuple(mode.value for mode in self.trust_modes)
+        map_stage = StageSpec(
+            stage_id="map",
+            kind=StageKind.MAP,
+            entry_point=self.map_entry_point,
+            needs=(),
+            inputs=self.map_stage_inputs,
+            outputs={"partial": self.partial_port},
+            parameter_names=self.map_parameter_names,
+            resources=resources,
+            execution=execution,
+            retry=RetryPolicy(),
+            verifier=_EXACT_ARTIFACT,
+            trust_modes=trust_values,
+            max_fan_out=limits.max_tasks,
+            cacheable=True,
+        )
+        reduce_input = PortSpec(
+            schema=self.partial_port.schema,
+            cardinality=Cardinality.MANY,
+            collection=CollectionKind.KEYED,
+        )
+        reduce_stage = StageSpec(
+            stage_id="reduce",
+            kind=StageKind.REDUCE,
+            entry_point=self.reduce_entry_point,
+            needs=("map",),
+            inputs={"partials": reduce_input},
+            outputs={"result": self.output_port},
+            parameter_names=self.reduce_parameter_names,
+            resources=resources,
+            execution=execution,
+            retry=RetryPolicy(),
+            verifier=_EXACT_ARTIFACT,
+            trust_modes=trust_values,
+            max_fan_out=1,
+            cacheable=True,
+        )
+        edges = [
+            ArtifactEdge(PortRef("input"), PortRef(port, "map"))
+            for port in self.map_stage_inputs
+        ] + [
+            ArtifactEdge(PortRef("partial", "map"), PortRef("partials", "reduce")),
+        ]
+        workflow = WorkflowSpec(
+            workflow_id=self.workflow_id or f"{name}-map-reduce-v1",
+            inputs={"input": self.input_port},
+            stages=(map_stage, reduce_stage),
+            edges=tuple(edges),
+            outputs={"result": PortRef("result", "reduce")},
+            max_tasks=limits.max_tasks,
+            max_output_bytes=limits.max_output_bytes,
+        )
+        self.manifest = WorkloadManifest(
+            sdk_api=VersionRange(">=1.0,<2.0"),
+            protocol=VersionRange(">=1,<2"),
+            workload=workload_id,
+            description=self.description,
+            package=PackageSpec("scimesh", package_digest),
+            environment=EnvironmentSpec(
+                "python-process",
+                environment_digest,
+                {"adapter": "sdk-native"},
+            ),
+            parameters_schema=self.parameters_schema,
+            workflow=workflow,
+            inputs={"input": self.input_port},
+            outputs={"result": self.output_port},
+            determinism=DeterminismProfile.BYTE_EXACT,
+            trust_modes=self.trust_modes,
+            verifier=VerifierSpec(_EXACT_ARTIFACT, {}),
+            limits=limits,
+            capabilities=self.capabilities,
+            conformance_profiles=("core-batch-v1",),
+        )
+        self._exact_verifier = _EXACT_VERIFIER
+        self._resources = resources
+        self._execution = execution
+        self._limits = limits
+
+    # ------------------------------------------------------------------
+    # Public assembly
+    # ------------------------------------------------------------------
+
+    def definition(self) -> WorkloadDefinition:
+        map_entry_point = self.map_entry_point
+        reduce_entry_point = self.reduce_entry_point
+        assert map_entry_point is not None and reduce_entry_point is not None
+        return WorkloadDefinition(
+            manifest=self.manifest,
+            planner=self,
+            runners={map_entry_point: self},
+            reducers={reduce_entry_point: self},
+            verifiers={_EXACT_ARTIFACT.canonical: self._exact_verifier},
+        )
+
+    # ------------------------------------------------------------------
+    # Scientific hooks
+    # ------------------------------------------------------------------
+
+    def domain_validate(self, parameters: Mapping[str, Any]) -> None:
+        """Extra job-parameter validation beyond the JSON schema."""
+
+    def resolved_parameters(self, request: JobRequest) -> dict[str, Any]:
+        """Values persisted as the plan's resolved parameters."""
+        return dict(request.parameters)
+
+    def partition_input(
+        self,
+        input_path: Path,
+        parameters: Mapping[str, Any],
+        workspace: Path,
+    ) -> list[Path]:
+        """Split the materialized input into deterministic shard files."""
+        raise NotImplementedError("partition_input must be implemented")
+
+    def plan_tasks(
+        self,
+        shard_paths: Sequence[Path],
+        resolved: Mapping[str, Any],
+        job: ValidatedJob,
+        negotiated: Any,
+        map_stage: StageSpec,
+        context: PlanningContext,
+    ) -> list[TaskSpec]:
+        """Build one map TaskSpec per planned shard."""
+        task_parameters = self.task_parameters(resolved)
+        tasks: list[TaskSpec] = []
+        for index, path in enumerate(shard_paths):
+            sealed = context.sink.seal(
+                path,
+                declaration=self.input_port.schema,
+            )
+            tasks.append(
+                self.task_spec(
+                    map_stage,
+                    job,
+                    negotiated,
+                    f"map/{index:08d}",
+                    task_parameters,
+                    {"input": ArtifactCollection.single(sealed)},
+                )
+            )
+        return tasks
+
+    def task_parameters(self, resolved: Mapping[str, Any]) -> dict[str, Any]:
+        """Project resolved parameters onto the map stage projection."""
+        return {
+            key: value
+            for key, value in resolved.items()
+            if key in set(self.map_parameter_names)
+        }
+
+    def compute_shard(
+        self,
+        inputs: Mapping[str, Path],
+        parameters: Mapping[str, Any],
+        output_path: Path,
+    ) -> Mapping[str, int | float]:
+        """Compute one map task and write its partial CSV."""
+        raise NotImplementedError("compute_shard must be implemented")
+
+    def parse_partial_key(self, key: str) -> Any:
+        """Parse one ``map.<key>`` partial key into an orderable identity."""
+        prefix = "map."
+        if not key.startswith(prefix):
+            raise ValueError("partial key must use map.<eight-digit-index>")
+        raw = key[len(prefix) :]
+        if len(raw) != 8 or not raw.isdigit():
+            raise ValueError("partial key must use map.<eight-digit-index>")
+        return int(raw)
+
+    def validate_partial_keys(self, parsed: Sequence[Any]) -> None:
+        """Enforce the reducer's partial-set invariant (default: contiguous)."""
+        indices = sorted(int(value) for value in parsed)
+        if indices != list(range(len(indices))):
+            raise ValueError("partial keys must be complete and contiguous")
+
+    def reduce_partials(
+        self,
+        partial_paths: Sequence[Path],
+        parameters: Mapping[str, Any],
+        output_path: Path,
+    ) -> Mapping[str, int | float]:
+        """Merge materialized partials into one deterministic final CSV."""
+        raise NotImplementedError("reduce_partials must be implemented")
+
+    # ------------------------------------------------------------------
+    # Framework handlers
+    # ------------------------------------------------------------------
+
+    def validate(self, request: JobRequest) -> ValidatedJob:
+        if request.workload != self.manifest.workload:
+            raise ValueError("workload received a request for another workload")
+        self.domain_validate(request.parameters)
+        return ValidatedJob(request, self.resolved_parameters(request))
+
+    def plan(self, job: ValidatedJob, context: PlanningContext) -> WorkflowPlan:
+        if not isinstance(job, ValidatedJob):
+            raise ValueError("job must be a ValidatedJob")
+        collection = job.request.inputs.get("input")
+        if collection is None:
+            raise ValueError("workload requires the input port")
+        self.input_port.validate_collection(collection, "job input")
+        input_path = context.catalog.materialize(collection.items[0].artifact)
+        workspace = context.workspace
+        workspace.mkdir(parents=True, exist_ok=True)
+        resolved = dict(job.resolved_parameters)
+        resolved = self.resolved_parameters_for_plan(job, input_path, resolved)
+        shard_paths = self.partition_input(input_path, resolved, workspace)
+        negotiated = context.negotiated
+        map_stage = self.manifest.workflow.stages[0]
+        tasks = self.plan_tasks(
+            shard_paths, resolved, job, negotiated, map_stage, context
+        )
+        return self.workflow_plan(job, negotiated, resolved, tasks)
+
+    def resolved_parameters_for_plan(
+        self,
+        job: ValidatedJob,
+        input_path: Path,
+        resolved: dict[str, Any],
+    ) -> dict[str, Any]:
+        """Hook to enrich resolved parameters at plan time (query resolution)."""
+        return resolved
+
+    def workflow_plan(
+        self,
+        job: ValidatedJob,
+        negotiated: Any,
+        resolved: Mapping[str, Any],
+        tasks: Sequence[TaskSpec],
+    ) -> WorkflowPlan:
+        return WorkflowPlan(
+            workload=self.manifest.workload,
+            package_digest=self.manifest.package.digest,
+            manifest_digest=self.manifest.digest,
+            trust_mode=job.request.trust_mode,
+            sdk_api_version=negotiated.sdk_api_version,
+            protocol_version=negotiated.protocol_version,
+            manifest_schema_version=self.manifest.manifest_schema_version,
+            workflow_schema_version=self.manifest.workflow.schema_version,
+            environment_digest=self.manifest.environment.digest,
+            verifier=self.manifest.verifier.verifier,
+            selected_features=negotiated.selected_features,
+            optional_fallbacks=negotiated.optional_fallbacks,
+            workflow_id=self.manifest.workflow.workflow_id,
+            resolved_parameters=dict(resolved),
+            tasks=tuple(tasks),
+        )
+
+    def task_spec(
+        self,
+        map_stage: StageSpec,
+        job: ValidatedJob,
+        negotiated: Any,
+        task_key: str,
+        parameters: Mapping[str, Any],
+        inputs: Mapping[str, ArtifactCollection],
+    ) -> TaskSpec:
+        assert map_stage.verifier is not None
+        return TaskSpec(
+            workload=self.manifest.workload,
+            package_digest=self.manifest.package.digest,
+            manifest_digest=self.manifest.digest,
+            trust_mode=job.request.trust_mode,
+            sdk_api_version=negotiated.sdk_api_version,
+            protocol_version=negotiated.protocol_version,
+            manifest_schema_version=self.manifest.manifest_schema_version,
+            workflow_schema_version=self.manifest.workflow.schema_version,
+            environment_digest=self.manifest.environment.digest,
+            verifier=map_stage.verifier,
+            selected_features=negotiated.selected_features,
+            optional_fallbacks=negotiated.optional_fallbacks,
+            task_key=task_key,
+            stage_id=map_stage.stage_id,
+            parameters=parameters,
+            inputs=inputs,
+            expected_outputs=map_stage.outputs,
+            resources=map_stage.resources,
+            execution=map_stage.execution,
+        ).validate_stage(map_stage)
+
+    def run(self, context: TaskContext) -> OutputManifest:
+        context.cancellation.raise_if_cancelled()
+        workspace = context.workspace
+        workspace.mkdir(parents=True, exist_ok=True)
+        inputs: dict[str, Path] = {}
+        for name, port in self.map_stage_inputs.items():
+            collection = context.task.inputs.get(name)
+            if collection is None:
+                raise ValueError(f"map task requires the {name} input")
+            port.validate_collection(collection, f"map input {name}")
+            assert collection.items
+            inputs[name] = context.catalog.materialize(collection.items[0].artifact)
+        output_path = workspace / "result.csv"
+        metrics = self.compute_shard(
+            inputs,
+            context.task.parameters,
+            output_path,
+        )
+        context.cancellation.raise_if_cancelled()
+        sealed = context.sink.seal(
+            output_path,
+            declaration=self.partial_port.schema,
+        )
+        return OutputManifest(
+            context.task.task_key,
+            {"partial": ArtifactCollection.single(sealed)},
+            metrics,
+            context.provenance,
+        ).validate_against(
+            context.task.expected_outputs,
+            max_output_bytes=self._limits.max_output_bytes,
+        )
+
+    def reduce(self, context: ReduceContext) -> OutputManifest:
+        context.cancellation.raise_if_cancelled()
+        collection = context.accepted_inputs.get("partials")
+        if collection is None:
+            raise ValueError("reducer requires a non-empty keyed partial collection")
+        if collection.kind is not CollectionKind.KEYED or not collection.items:
+            raise ValueError("reducer requires a non-empty keyed partial collection")
+        self.manifest.workflow.stages[1].inputs["partials"].validate_collection(
+            collection,
+            "reducer partials",
+        )
+        parsed = [self.parse_partial_key(item.key or "") for item in collection.items]
+        self.validate_partial_keys(parsed)
+        expected_keys = context.task.expected_input_keys.get("partials")
+        if expected_keys is None or {item.key for item in collection.items} != set(
+            expected_keys
+        ):
+            raise ValueError("partial keys do not match the coordinator expected set")
+        workspace = context.workspace
+        workspace.mkdir(parents=True, exist_ok=True)
+        partial_paths: list[Path] = []
+        for index, item in sorted(
+            enumerate(collection.items),
+            key=lambda entry: entry[1].key or "",
+        ):
+            artifact: ArtifactRef = item.artifact
+            source = context.catalog.materialize(artifact)
+            target = workspace / artifact.artifact_id
+            if source.resolve() != target.resolve():
+                shutil.copyfile(source, target)
+            if _sha256_file(target) != artifact.sha256:
+                raise ValueError("materialized partial checksum does not match")
+            partial_paths.append(target)
+        result_path = workspace / "result.csv"
+        metrics = self.reduce_partials(
+            partial_paths,
+            context.task.parameters,
+            result_path,
+        )
+        context.cancellation.raise_if_cancelled()
+        sealed = context.sink.seal(
+            result_path,
+            declaration=self.output_port.schema,
+        )
+        return OutputManifest(
+            context.task.task_key,
+            {"result": ArtifactCollection.single(sealed)},
+            metrics,
+            context.provenance,
+        ).validate_against(
+            context.task.expected_outputs,
+            max_output_bytes=self._limits.max_output_bytes,
+        )

scimesh/sdk/registry.py

@@ -24,8 +24,20 @@ from .identity import ComponentRef, WorkloadId
 from .integrity import installed_distribution_digest
 from .manifest import WorkloadManifest
 from .plans import JobRequest, ValidatedJob, WorkflowPlan
-from .protocols import Planner, PlanningContext, PlanningResources, Reducer, Runner, Verifier
+from .protocols import (
-from .runtime import CompatibilityError, NegotiatedWorkload, RuntimeCapabilities, negotiate_manifest
+    Planner,
+    PlanningContext,
+    PlanningResources,
+    Reducer,
+    Runner,
+    Verifier,
+)
+from .runtime import (
+    CompatibilityError,
+    NegotiatedWorkload,
+    RuntimeCapabilities,
+    negotiate_manifest,
+)
 from .schema import validate_parameter_instance
 from .workflow import StageKind
 
@@ -51,11 +63,11 @@ def _validate_entry_point_ownership(entry_point: metadata.EntryPoint) -> None:
         raise ValueError("workload entry point has an invalid module path")
 
     raw_top_level = distribution.read_text("top_level.txt")
-    declared = {
+    declared = (
-        line.strip()
+        {line.strip() for line in raw_top_level.splitlines() if line.strip()}
-        for line in raw_top_level.splitlines()
+        if raw_top_level is not None
-        if line.strip()
+        else set()
-    } if raw_top_level is not None else set()
+    )
     root_name = parts[0]
     if root_name not in declared:
         raise ValueError("workload entry point module is outside its distribution")
@@ -81,9 +93,18 @@ def _validate_entry_point_ownership(entry_point: metadata.EntryPoint) -> None:
         ownership_root = package_root.resolve()
         candidates = [
             *(Path(str(module_base) + suffix) for suffix in machinery.SOURCE_SUFFIXES),
-            *(Path(str(module_base) + suffix) for suffix in machinery.EXTENSION_SUFFIXES),
+            *(
-            *(module_base / ("__init__" + suffix) for suffix in machinery.SOURCE_SUFFIXES),
+                Path(str(module_base) + suffix)
-            *(module_base / ("__init__" + suffix) for suffix in machinery.EXTENSION_SUFFIXES),
+                for suffix in machinery.EXTENSION_SUFFIXES
+            ),
+            *(
+                module_base / ("__init__" + suffix)
+                for suffix in machinery.SOURCE_SUFFIXES
+            ),
+            *(
+                module_base / ("__init__" + suffix)
+                for suffix in machinery.EXTENSION_SUFFIXES
+            ),
         ]
     else:
         if len(parts) != 1:
@@ -92,7 +113,10 @@ def _validate_entry_point_ownership(entry_point: metadata.EntryPoint) -> None:
         module_base = Path(distribution.locate_file(root_name))
         candidates = [
             *(Path(str(module_base) + suffix) for suffix in machinery.SOURCE_SUFFIXES),
-            *(Path(str(module_base) + suffix) for suffix in machinery.EXTENSION_SUFFIXES),
+            *(
+                Path(str(module_base) + suffix)
+                for suffix in machinery.EXTENSION_SUFFIXES
+            ),
         ]
     existing = tuple(candidate for candidate in candidates if candidate.is_file())
     if len(existing) != 1 or not existing[0].resolve().is_relative_to(ownership_root):
@@ -126,7 +150,9 @@ class WorkloadDefinition:
             for name, handler in values.items():
                 canonical = require_string(name, f"{field} entry point", max_length=256)
                 if not callable(getattr(handler, method, None)):
-                    raise ValueError(f"definition {field} handler must implement {method}")
+                    raise ValueError(
+                        f"definition {field} handler must implement {method}"
+                    )
                 copied[canonical] = handler
             object.__setattr__(self, field, MappingProxyType(copied))
         for stage in self.manifest.workflow.stages:
@@ -149,23 +175,39 @@ class WorkloadDefinition:
                 )
         verifier_key = self.manifest.verifier.verifier.canonical
         if verifier_key not in self.verifiers:
-            raise ValueError(f"definition has no installed manifest verifier: {verifier_key}")
+            raise ValueError(
+                f"definition has no installed manifest verifier: {verifier_key}"
+            )
         for key, verifier in self.verifiers.items():
             try:
                 declared_identity = ComponentRef.from_dict(key)
             except ValueError as error:
-                raise ValueError("definition verifier keys must be component identities") from error
+                raise ValueError(
-            if declared_identity.canonical != key or getattr(verifier, "identity", None) != declared_identity:
+                    "definition verifier keys must be component identities"
-                raise ValueError("definition verifier handler identity does not match its key")
+                ) from error
+            if (
+                declared_identity.canonical != key
+                or getattr(verifier, "identity", None) != declared_identity
+            ):
+                raise ValueError(
+                    "definition verifier handler identity does not match its key"
+                )
         manifest_verifier = self.verifiers[verifier_key]
         handler_configuration = getattr(manifest_verifier, "configuration", None)
         if handler_configuration is None:
             if self.manifest.verifier.configuration:
-                raise ValueError("manifest verifier configuration is not bound by its handler")
+                raise ValueError(
+                    "manifest verifier configuration is not bound by its handler"
+                )
         elif dict(handler_configuration) != dict(self.manifest.verifier.configuration):
-            raise ValueError("manifest verifier configuration does not match its handler")
+            raise ValueError(
+                "manifest verifier configuration does not match its handler"
+            )
         for stage in self.manifest.workflow.stages:
-            if stage.verifier is not None and stage.verifier.canonical not in self.verifiers:
+            if (
+                stage.verifier is not None
+                and stage.verifier.canonical not in self.verifiers
+            ):
                 raise ValueError(
                     f"definition has no installed stage verifier: {stage.verifier.canonical}"
                 )
@@ -178,13 +220,54 @@ class AllowedPackage:
     digest: str
 
     def __post_init__(self) -> None:
-        distribution = require_string(self.distribution, "distribution", max_length=128).lower()
+        distribution = require_string(
+            self.distribution, "distribution", max_length=128
+        ).lower()
         if not re.fullmatch(r"[a-z0-9]+(?:[-_.][a-z0-9]+)*", distribution):
-            raise ValueError("distribution must be a canonical Python distribution name")
+            raise ValueError(
+                "distribution must be a canonical Python distribution name"
+            )
         object.__setattr__(self, "distribution", distribution.replace("_", "-"))
         if not isinstance(self.workload, WorkloadId):
             raise ValueError("allowed workload must be a WorkloadId")
-        object.__setattr__(self, "digest", require_sha256(self.digest, "allowed digest", prefixed=True))
+        object.__setattr__(
+            self, "digest", require_sha256(self.digest, "allowed digest", prefixed=True)
+        )
+
+
+def workload_allowlist_from_json(value: object) -> tuple[AllowedPackage, ...]:
+    """Parse a JSON array of ``{distribution, name, version, digest}`` allowlist entries."""
+    import json
+
+    if value is None or value == "":
+        return ()
+    if not isinstance(value, str):
+        raise ValueError("workload allowlist must be a JSON array")
+    try:
+        decoded = json.loads(value)
+    except (TypeError, json.JSONDecodeError, RecursionError) as error:
+        raise ValueError("workload allowlist must be valid JSON") from error
+    if not isinstance(decoded, list):
+        raise ValueError("workload allowlist must be a JSON array")
+    entries: list[AllowedPackage] = []
+    for item in decoded:
+        if not isinstance(item, dict) or not {
+            "distribution",
+            "name",
+            "version",
+            "digest",
+        }.issubset(item):
+            raise ValueError(
+                "workload allowlist entries need distribution, name, version, and digest"
+            )
+        entries.append(
+            AllowedPackage(
+                str(item["distribution"]),
+                WorkloadId(str(item["name"]), str(item["version"])),
+                str(item["digest"]),
+            )
+        )
+    return tuple(entries)
 
 
 @dataclass(frozen=True, slots=True)
@@ -223,14 +306,18 @@ class WorkloadRegistry:
         self._enabled: set[tuple[str, str, str]] = set()
         self._lock = RLock()
 
-    def register(self, definition: WorkloadDefinition, *, enabled: bool = False) -> None:
+    def register(
+        self, definition: WorkloadDefinition, *, enabled: bool = False
+    ) -> None:
         if not isinstance(definition, WorkloadDefinition):
             raise ValueError("definition must be a WorkloadDefinition")
         workload = definition.manifest.workload
         key = (workload.name, workload.version)
         with self._lock:
             if key in self._definitions:
-                raise ValueError(f"workload version already registered: {workload.name}@{workload.version}")
+                raise ValueError(
+                    f"workload version already registered: {workload.name}@{workload.version}"
+                )
             self._definitions[key] = definition
             if enabled:
                 self._enabled.add((*key, definition.manifest.package.digest))
@@ -240,7 +327,9 @@ class WorkloadRegistry:
         with self._lock:
             definition = self._registered(name, version)
             if digest != definition.manifest.package.digest:
-                raise ValueError("package digest does not match the registered manifest")
+                raise ValueError(
+                    "package digest does not match the registered manifest"
+                )
             self._enabled.add((definition.manifest.workload.name, version, digest))
 
     def disable(self, name: str, version: str, package_digest: str) -> None:
@@ -257,7 +346,9 @@ class WorkloadRegistry:
             try:
                 return self._definitions[(canonical, version)]
             except KeyError as error:
-                raise ValueError(f"unknown workload version: {canonical}@{version}") from error
+                raise ValueError(
+                    f"unknown workload version: {canonical}@{version}"
+                ) from error
 
     def require(
         self,
@@ -270,10 +361,21 @@ class WorkloadRegistry:
         digest = require_sha256(package_digest, "package_digest", prefixed=True)
         with self._lock:
             definition = self._registered(name, version)
-            identity = (definition.manifest.workload.name, definition.manifest.workload.version, digest)
+            identity = (
-            if digest != definition.manifest.package.digest or identity not in self._enabled:
+                definition.manifest.workload.name,
+                definition.manifest.workload.version,
+                digest,
+            )
+            if (
+                digest != definition.manifest.package.digest
+                or identity not in self._enabled
+            ):
                 raise ValueError("workload package digest is not enabled")
-        negotiated = negotiate_manifest(definition.manifest, runtime) if runtime is not None else None
+        negotiated = (
+            negotiate_manifest(definition.manifest, runtime)
+            if runtime is not None
+            else None
+        )
         return definition, negotiated
 
     def plan(
@@ -293,31 +395,41 @@ class WorkloadRegistry:
             runtime=runtime,
         )
         assert negotiated is not None
-        self._validate_request_compatibility(request, definition.manifest, runtime, negotiated)
+        self._validate_request_compatibility(
+            request, definition.manifest, runtime, negotiated
+        )
         self._validate_request_shape(request, definition.manifest)
         validated = definition.planner.validate(request)
         if not isinstance(validated, ValidatedJob) or validated.request != request:
-            raise ValueError("planner.validate must return a ValidatedJob for the same request")
+            raise ValueError(
+                "planner.validate must return a ValidatedJob for the same request"
+            )
         plan = definition.planner.plan(
             validated,
             _NegotiatedPlanningContext(context, negotiated),
         )
         if not isinstance(plan, WorkflowPlan) or plan.workload != request.workload:
-            raise ValueError("planner.plan must return a WorkflowPlan for the requested workload")
+            raise ValueError(
+                "planner.plan must return a WorkflowPlan for the requested workload"
+            )
         if (
             plan.package_digest != definition.manifest.package.digest
             or plan.manifest_digest != definition.manifest.digest
             or plan.trust_mode is not request.trust_mode
             or plan.sdk_api_version != runtime.sdk_api_version
             or plan.protocol_version != runtime.protocol_version
-            or plan.manifest_schema_version != definition.manifest.manifest_schema_version
+            or plan.manifest_schema_version
-            or plan.workflow_schema_version != definition.manifest.workflow.schema_version
+            != definition.manifest.manifest_schema_version
+            or plan.workflow_schema_version
+            != definition.manifest.workflow.schema_version
             or plan.environment_digest != definition.manifest.environment.digest
             or plan.verifier != definition.manifest.verifier.verifier
             or plan.selected_features != negotiated.selected_features
             or plan.optional_fallbacks != negotiated.optional_fallbacks
         ):
-            raise ValueError("planner plan does not carry the selected immutable workload pin")
+            raise ValueError(
+                "planner plan does not carry the selected immutable workload pin"
+            )
         plan.validate_workflow(definition.manifest.workflow)
         self._validate_plan_limits(request, plan, definition.manifest)
         return WorkflowPlan.from_json(plan.to_json())
@@ -369,7 +481,9 @@ class WorkloadRegistry:
                 )
 
     @staticmethod
-    def _validate_request_shape(request: JobRequest, manifest: WorkloadManifest) -> None:
+    def _validate_request_shape(
+        request: JobRequest, manifest: WorkloadManifest
+    ) -> None:
         if set(request.inputs) != set(manifest.inputs):
             raise ValueError("job input ports do not match the manifest")
         total_bytes = 0
@@ -380,7 +494,9 @@ class WorkloadRegistry:
             for item in request.inputs[name].items:
                 existing = artifact_references.get(item.artifact.artifact_id)
                 if existing is not None and existing != item.artifact:
-                    raise ValueError("job reuses an artifact ID with conflicting metadata")
+                    raise ValueError(
+                        "job reuses an artifact ID with conflicting metadata"
+                    )
                 artifact_references[item.artifact.artifact_id] = item.artifact
         if total_bytes > manifest.limits.max_input_bytes:
             raise ValueError("job inputs exceed the manifest byte limit")
@@ -388,7 +504,15 @@ class WorkloadRegistry:
             raise ValueError("job inputs exceed the manifest artifact limit")
         import json
         from ._validation import thaw_json
-        if len(json.dumps(thaw_json(request.parameters), allow_nan=False).encode("utf-8")) > manifest.limits.max_parameter_bytes:
+
+        if (
+            len(
+                json.dumps(thaw_json(request.parameters), allow_nan=False).encode(
+                    "utf-8"
+                )
+            )
+            > manifest.limits.max_parameter_bytes
+        ):
             raise ValueError("job parameters exceed the manifest byte limit")
         validate_parameter_instance(request.parameters, manifest.parameters_schema)
 
@@ -408,13 +532,23 @@ class WorkloadRegistry:
                 for item in collection.items:
                     existing = references.get(item.artifact.artifact_id)
                     if existing is not None and existing != item.artifact:
-                        raise ValueError("workflow plan reuses an artifact ID with conflicting metadata")
+                        raise ValueError(
+                            "workflow plan reuses an artifact ID with conflicting metadata"
+                        )
                     references[item.artifact.artifact_id] = item.artifact
-            if len(canonical_json(task.parameters).encode("utf-8")) > manifest.limits.max_parameter_bytes:
+            if (
-                raise ValueError("planned task parameters exceed the manifest byte limit")
+                len(canonical_json(task.parameters).encode("utf-8"))
+                > manifest.limits.max_parameter_bytes
+            ):
+                raise ValueError(
+                    "planned task parameters exceed the manifest byte limit"
+                )
         if len(references) > manifest.limits.max_artifacts:
             raise ValueError("workflow plan exceeds the manifest artifact limit")
-        if len(canonical_json(plan.resolved_parameters).encode("utf-8")) > manifest.limits.max_parameter_bytes:
+        if (
+            len(canonical_json(plan.resolved_parameters).encode("utf-8"))
+            > manifest.limits.max_parameter_bytes
+        ):
             raise ValueError("resolved parameters exceed the manifest byte limit")
 
     def descriptions(self) -> tuple[WorkloadDescription, ...]:
@@ -455,7 +589,10 @@ class WorkloadRegistry:
             for key, approval in allowed.items():
                 if _normalized_distribution_name(key[0]) != distribution:
                     continue
-                if entry_point.name != f"{approval.workload.name}@{approval.workload.version}":
+                if (
+                    entry_point.name
+                    != f"{approval.workload.name}@{approval.workload.version}"
+                ):
                     continue
                 _validate_entry_point_ownership(entry_point)
                 # Import policy is process-global, so installed discovery is
@@ -463,9 +600,12 @@ class WorkloadRegistry:
                 # cache prefix prevents pre-existing package pyc files from
                 # being consumed, while dont_write_bytecode keeps the
                 # measured source tree unchanged during both load and factory.
-                with _DISCOVERY_IMPORT_LOCK, TemporaryDirectory(
+                with (
-                    prefix="scimesh-discovery-cache-"
+                    _DISCOVERY_IMPORT_LOCK,
-                ) as cache_prefix:
+                    TemporaryDirectory(
+                        prefix="scimesh-discovery-cache-"
+                    ) as cache_prefix,
+                ):
                     measured_before = installed_distribution_digest(entry_point.dist)
                     if measured_before != approval.digest:
                         raise ValueError(
@@ -479,44 +619,64 @@ class WorkloadRegistry:
                         loaded = entry_point.load()
                         definition = (
                             loaded()
-                            if callable(loaded) and not isinstance(loaded, WorkloadDefinition)
+                            if callable(loaded)
+                            and not isinstance(loaded, WorkloadDefinition)
                             else loaded
                         )
                     finally:
                         sys.pycache_prefix = previous_cache_prefix
                         sys.dont_write_bytecode = previous_bytecode_policy
-                    if installed_distribution_digest(entry_point.dist) != measured_before:
+                    if (
+                        installed_distribution_digest(entry_point.dist)
+                        != measured_before
+                    ):
                         raise ValueError(
                             "installed package content changed while loading its entry point"
                         )
                 if not isinstance(definition, WorkloadDefinition):
-                    raise ValueError("workload entry point must provide a WorkloadDefinition")
+                    raise ValueError(
+                        "workload entry point must provide a WorkloadDefinition"
+                    )
                 if definition.manifest.workload != approval.workload:
-                    raise ValueError("discovered workload identity does not match its allowlist entry")
+                    raise ValueError(
+                        "discovered workload identity does not match its allowlist entry"
+                    )
                 if definition.manifest.package.distribution != approval.distribution:
-                    raise ValueError("discovered package identity does not match its allowlist entry")
+                    raise ValueError(
+                        "discovered package identity does not match its allowlist entry"
+                    )
                 if definition.manifest.package.digest != approval.digest:
-                    raise ValueError("discovered package digest does not match its allowlist entry")
+                    raise ValueError(
+                        "discovered package digest does not match its allowlist entry"
+                    )
                 if key in discovered:
-                    raise ValueError("multiple installed entry points match one allowlist entry")
+                    raise ValueError(
+                        "multiple installed entry points match one allowlist entry"
+                    )
                 pending.append(definition)
                 discovered.add(key)
                 break
         missing = sorted(set(allowed) - discovered)
         if missing:
             identities = ", ".join(f"{name}@{version}" for _, name, version in missing)
-            raise ValueError("allowlisted workload entry points were not installed: " + identities)
+            raise ValueError(
+                "allowlisted workload entry points were not installed: " + identities
+            )
         pending_keys = [
             (definition.manifest.workload.name, definition.manifest.workload.version)
             for definition in pending
         ]
         if len(pending_keys) != len(set(pending_keys)):
-            raise ValueError("multiple allowlisted distributions provide one workload version")
+            raise ValueError(
+                "multiple allowlisted distributions provide one workload version"
+            )
         with self._lock:
             conflicts = [key for key in pending_keys if key in self._definitions]
             if conflicts:
                 name, version = conflicts[0]
-                raise ValueError(f"workload version already registered: {name}@{version}")
+                raise ValueError(
+                    f"workload version already registered: {name}@{version}"
+                )
             definitions = dict(self._definitions)
             enabled = set(self._enabled)
             for key, definition in zip(pending_keys, pending):

scimesh/worker/cli.py

@@ -77,7 +77,9 @@ def main(argv: list[str] | None = None) -> int:
         config = WorkerConfig.from_environment(overrides)
     except (TypeError, ValueError) as error:
         parser.error(str(error))
-    logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s")
+    logging.basicConfig(
+        level=logging.INFO, format="%(asctime)s %(levelname)s %(message)s"
+    )
     # One shared token strategy backs both clients: a worker key (exchanged and
     # refreshed) or a static bearer token, decided by what the config carries.
     tokens = provider_from_config(
@@ -95,7 +97,7 @@ def main(argv: list[str] | None = None) -> int:
         HttpArtifactClient(
             config.coordinator_url, config.request_timeout, token_provider=tokens
         ),
-        SciMeshRunner(),
+        SciMeshRunner.for_worker(config),
     ).run_forever()
     return 0 if completed_without_interruption else 130
 

scimesh/worker/config.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import json
 from dataclasses import dataclass
 from math import isfinite
 from pathlib import Path
@@ -10,6 +11,8 @@ import socket
 from typing import Mapping
 from urllib.parse import urlsplit
 
+from scimesh.sdk.registry import AllowedPackage, workload_allowlist_from_json
+
 
 def _clean_url(value: object | None) -> str | None:
     """Normalise an optional URL: drop a blank one, strip a trailing slash."""
@@ -31,6 +34,24 @@ def _positive_number(value: object, name: str, *, allow_zero: bool = False) -> N
         raise ValueError(f"{name} must be {qualifier}")
 
 
+def _capabilities(value: object) -> tuple[str, ...]:
+    """Parse a comma-separated capability list into unique non-empty names."""
+    if value is None:
+        return ("similarity-search", "similarity_search")
+    if not isinstance(value, str) or not value.strip():
+        raise ValueError("capabilities must be a comma-separated list")
+    names = tuple(
+        dict.fromkeys(item.strip() for item in value.split(",") if item.strip())
+    )
+    if not names:
+        raise ValueError("capabilities cannot be empty")
+    return names
+
+
+def _workload_allowlist(value: object) -> tuple[AllowedPackage, ...]:
+    return workload_allowlist_from_json(value)
+
+
 @dataclass(frozen=True)
 class WorkerConfig:
     coordinator_url: str
@@ -60,6 +81,11 @@ class WorkerConfig:
         "similarity-search",
         "similarity_search",
     )
+    # Optional allowlist of installed SDK workload packages to execute. When
+    # empty, the worker runs the built-in similarity-search only. Entries are
+    # ``{distribution, name, version, digest}`` JSON objects matching the
+    # installed ``scimesh.workloads`` entry points.
+    workload_allowlist: tuple[AllowedPackage, ...] = ()
 
     def __post_init__(self) -> None:
         parsed = urlsplit(self.coordinator_url)
@@ -72,8 +98,14 @@ class WorkerConfig:
             if us.scheme not in {"http", "https"} or not us.hostname:
                 raise ValueError("userservice_url must be an absolute HTTP(S) URL")
         if self.worker_key is not None and not self.userservice_url:
-            raise ValueError("worker_key requires userservice_url (SCIMESH_USERSERVICE_URL)")
+            raise ValueError(
-        if isinstance(self.cpu_count, bool) or not isinstance(self.cpu_count, int) or self.cpu_count < 1:
+                "worker_key requires userservice_url (SCIMESH_USERSERVICE_URL)"
+            )
+        if (
+            isinstance(self.cpu_count, bool)
+            or not isinstance(self.cpu_count, int)
+            or self.cpu_count < 1
+        ):
             raise ValueError("cpu_count must be positive")
         if self.worker_id is not None and not isinstance(self.worker_id, str):
             raise ValueError("worker_id must be a string when set")
@@ -87,7 +119,9 @@ class WorkerConfig:
         _positive_number(self.request_timeout, "request_timeout")
         _positive_number(self.heartbeat_interval, "heartbeat_interval")
         if self.cleanup_after_seconds is not None:
-            _positive_number(self.cleanup_after_seconds, "cleanup_after_seconds", allow_zero=True)
+            _positive_number(
+                self.cleanup_after_seconds, "cleanup_after_seconds", allow_zero=True
+            )
         if self.max_tasks is not None:
             if (
                 isinstance(self.max_tasks, bool)
@@ -99,6 +133,18 @@ class WorkerConfig:
             raise ValueError("exit_when_idle must be a boolean")
         if not self.capabilities:
             raise ValueError("capabilities cannot be empty")
+        if any(
+            not isinstance(capability, str) or not capability.strip()
+            for capability in self.capabilities
+        ):
+            raise ValueError("capabilities must contain non-empty names")
+        if len(self.capabilities) != len(set(self.capabilities)):
+            raise ValueError("capabilities must be unique")
+        if any(
+            not isinstance(package, AllowedPackage)
+            for package in self.workload_allowlist
+        ):
+            raise ValueError("workload_allowlist must contain AllowedPackage values")
         # Runner subprocesses use a task directory as their cwd. Keep the
         # configured root absolute so input/output paths remain valid there
         # even when the CLI received a convenient relative --work-dir value.
@@ -111,7 +157,9 @@ class WorkerConfig:
         """Build config from environment, allowing typed CLI values to override it."""
         values = overrides or {}
 
-        def value(name: str, environment: str, default: object | None = None) -> object | None:
+        def value(
+            name: str, environment: str, default: object | None = None
+        ) -> object | None:
             override = values.get(name)
             return override if override is not None else os.getenv(environment, default)
 
@@ -122,20 +170,37 @@ class WorkerConfig:
         cpu_count = value("cpu_count", "SCIMESH_CPU_COUNT", os.cpu_count() or 1)
         memory_mb = value("memory_mb", "SCIMESH_MEMORY_MB")
         max_tasks = value("max_tasks", "SCIMESH_MAX_TASKS")
+        capabilities = value("capabilities", "SCIMESH_CAPABILITIES")
+        allowlist = value("workload_allowlist", "SCIMESH_WORKLOAD_ALLOWLIST")
+        worker_id = value("worker_id", "SCIMESH_WORKER_ID")
+        work_dir = value("work_dir", "SCIMESH_WORK_DIR", "./scimesh-worker-data")
+        worker_name = value("worker_name", "SCIMESH_WORKER_NAME", socket.gethostname())
+        poll_interval = value("poll_interval", "SCIMESH_POLL_INTERVAL", "2")
+        request_timeout = value("request_timeout", "SCIMESH_REQUEST_TIMEOUT", "30")
+        heartbeat_interval = value(
+            "heartbeat_interval", "SCIMESH_HEARTBEAT_INTERVAL", "15"
+        )
+        bearer_token = value("bearer_token", "SCIMESH_BEARER_TOKEN")
+        worker_key = value("worker_key", "SCIMESH_WORKER_KEY")
+        userservice_url = _clean_url(
+            value("userservice_url", "SCIMESH_USERSERVICE_URL")
+        )
         return cls(
             coordinator_url=url.rstrip("/"),
-            worker_id=value("worker_id", "SCIMESH_WORKER_ID"),
+            worker_id=str(worker_id) if worker_id is not None else None,
-            work_dir=Path(value("work_dir", "SCIMESH_WORK_DIR", "./scimesh-worker-data")),
+            work_dir=Path(str(work_dir)),
-            worker_name=str(value("worker_name", "SCIMESH_WORKER_NAME", socket.gethostname())),
+            worker_name=str(worker_name),
             cpu_count=int(cpu_count),
             memory_mb=int(memory_mb) if memory_mb is not None else None,
-            poll_interval=float(value("poll_interval", "SCIMESH_POLL_INTERVAL", "2")),
+            poll_interval=float(poll_interval),
-            request_timeout=float(value("request_timeout", "SCIMESH_REQUEST_TIMEOUT", "30")),
+            request_timeout=float(request_timeout),
-            heartbeat_interval=float(value("heartbeat_interval", "SCIMESH_HEARTBEAT_INTERVAL", "15")),
+            heartbeat_interval=float(heartbeat_interval),
-            bearer_token=value("bearer_token", "SCIMESH_BEARER_TOKEN"),
+            bearer_token=str(bearer_token) if bearer_token is not None else None,
-            worker_key=value("worker_key", "SCIMESH_WORKER_KEY"),
+            worker_key=str(worker_key) if worker_key is not None else None,
-            userservice_url=_clean_url(value("userservice_url", "SCIMESH_USERSERVICE_URL")),
+            userservice_url=userservice_url,
             cleanup_after_seconds=float(cleanup) if cleanup else None,
             max_tasks=int(max_tasks) if max_tasks is not None else None,
             exit_when_idle=bool(values.get("exit_when_idle", False)),
+            capabilities=_capabilities(capabilities),
+            workload_allowlist=_workload_allowlist(allowlist),
         )

scimesh/worker/runners.py

@@ -3,13 +3,20 @@
 The runner is a v1-wire bridge: the coordinator still claims flat tasks and
 the worker still uploads one partial CSV, but execution goes through the
 SDK-built workload's own Runner handler with a real ``TaskSpec``,
-provenance, resource reservation, and a content-addressed local store. No
+provenance, resource reservation, and a content-addressed local store.
-legacy distributed-protocol code is involved.
+
+The runner is workload-generic: it loads definitions by name (from an
+explicit mapping, built-in defaults, or installed-package discovery through
+an administrator allowlist) and executes any workload whose map stage has a
+single ``input`` port and a single ``partial`` output. Anything else fails
+closed with a clear message, so adding a workload never requires touching
+worker code.
 """
 
 from __future__ import annotations
 
 import hashlib
+import platform
 from datetime import datetime, timezone
 from pathlib import Path
 from typing import Mapping, Protocol
@@ -28,28 +35,21 @@ from scimesh.sdk.conformance import (
     ScopedArtifactSink,
 )
 from scimesh.sdk._validation import canonical_json
+from scimesh.sdk.identity import SDK_API_VERSION
 from scimesh.sdk.manifest import TrustMode
 from scimesh.sdk.plans import TaskSpec
-from scimesh.sdk.registry import WorkloadDefinition
+from scimesh.sdk.registry import WorkloadDefinition, WorkloadRegistry
-from scimesh.sdk.resources import ResourceAllocation, ResourcePool
+from scimesh.sdk.resources import ResourceAllocation, ResourceInventory, ResourcePool
 from scimesh.sdk.runtime import (
     NegotiatedWorkload,
     RuntimeCapabilities,
     negotiate_manifest,
 )
 from scimesh.sdk.workflow import StageKind
-from scimesh.workloads.library import default_sdk_runtime
-from scimesh.workloads.search import similarity_search_sdk_definition
 
+from .config import WorkerConfig
 from .models import ClaimedTask, ProducedArtifact, RunResult
 
-#: Parameters the worker may hand to a map task. ``max_rows`` is a plan-time
-#: option applied before sharding and is intentionally rejected here.
-_RUNNER_PARAMETERS = frozenset(
-    {"query_smiles", "top_k", "threshold", "threshold_direction", "progress_every"}
-)
-
-
 def _utc_now() -> str:
     return datetime.now(timezone.utc).isoformat().replace("+00:00", "Z")
 
@@ -58,22 +58,93 @@ class Runner(Protocol):
     def run(self, task: ClaimedTask, task_dir: Path) -> RunResult: ...
 
 
+def _inventory_for(
+    definitions: Mapping[str, WorkloadDefinition],
+    *,
+    cpu_cores: int,
+    memory_mb: int,
+) -> ResourceInventory:
+    return ResourceInventory(
+        cpu_cores=cpu_cores,
+        memory_mb=memory_mb,
+        scratch_mb=memory_mb,
+        architecture=platform.machine().lower() or "unknown",
+        environment_digests=tuple(
+            dict.fromkeys(
+                definition.manifest.environment.digest
+                for definition in definitions.values()
+            )
+        ),
+    )
+
+
+def _runtime_for(
+    definitions: Mapping[str, WorkloadDefinition], inventory: ResourceInventory
+) -> RuntimeCapabilities:
+    return RuntimeCapabilities(
+        sdk_api_version=SDK_API_VERSION,
+        protocol_version="1.0.0",
+        profiles=("core-batch-v1",),
+        features={"artifact-collections": "1.0.0", "exact-verifier": "1.0.0"},
+        workload_capabilities=tuple(sorted(definitions)),
+        inventory=inventory,
+    )
+
+
 class SciMeshRunner:
-    """Execute claimed coordinator tasks through the SDK-built workloads."""
+    """Execute claimed coordinator tasks through SDK-built workloads."""
 
     def __init__(
         self,
         definitions: Mapping[str, WorkloadDefinition] | None = None,
+        *,
+        inventory: ResourceInventory | None = None,
         runtime: RuntimeCapabilities | None = None,
     ) -> None:
         self._definitions = dict(definitions or {})
         if "similarity-search" not in self._definitions:
+            from scimesh.workloads.search import similarity_search_sdk_definition
+
             self._definitions["similarity-search"] = (
                 similarity_search_sdk_definition().definition()
             )
-        self._runtime = runtime or default_sdk_runtime()
+        self._inventory = inventory or _inventory_for(
+            self._definitions,
+            cpu_cores=1,
+            memory_mb=1024,
+        )
+        self._runtime = runtime or _runtime_for(self._definitions, self._inventory)
         self._pool = ResourcePool(self._runtime.inventory, max_concurrency=1)
 
+    @classmethod
+    def for_worker(cls, config: WorkerConfig) -> "SciMeshRunner":
+        """Build a runner for one worker: discover allowlisted workloads or use built-ins."""
+        definitions: dict[str, WorkloadDefinition] = {}
+        if config.workload_allowlist:
+            registry = WorkloadRegistry()
+            registry.discover_installed(config.workload_allowlist)
+            for description in registry.descriptions():
+                definition, _ = registry.require(
+                    description.workload.name,
+                    description.workload.version,
+                    description.package_digest,
+                )
+                definitions[description.workload.name] = definition
+            if not definitions:
+                raise ValueError("workload_allowlist discovered no workloads")
+        else:
+            from scimesh.workloads.search import similarity_search_sdk_definition
+
+            definitions["similarity-search"] = (
+                similarity_search_sdk_definition().definition()
+            )
+        inventory = _inventory_for(
+            definitions,
+            cpu_cores=config.cpu_count,
+            memory_mb=config.memory_mb or 1024,
+        )
+        return cls(definitions=definitions, inventory=inventory)
+
     def run(self, task: ClaimedTask, task_dir: Path) -> RunResult:
         task_dir = task_dir.resolve()
         workload = task.workload.replace("_", "-")
@@ -85,11 +156,14 @@ class SciMeshRunner:
         map_stage = next(
             stage for stage in manifest.workflow.stages if stage.kind is StageKind.MAP
         )
+        if set(map_stage.inputs) != {"input"} or len(map_stage.outputs) != 1:
+            raise ValueError(
+                f"workload {workload} is not executable through the v1 single-input contract"
+            )
         assert map_stage.verifier is not None
         input_path = task_dir / "input"
         if not input_path.is_file():
             raise ValueError("claimed task input is missing")
-        parameters = self._resolve_parameters(task, input_path)
         store = LocalArtifactStore(task_dir / "sdk-store")
         input_ref = store.import_file(
             input_path,
@@ -110,7 +184,7 @@ class SciMeshRunner:
             optional_fallbacks=negotiated.optional_fallbacks,
             task_key="map/00000000",
             stage_id=map_stage.stage_id,
-            parameters=parameters,
+            parameters=task.parameters,
             inputs={"input": ArtifactCollection.single(input_ref)},
             expected_outputs=map_stage.outputs,
             resources=map_stage.resources,
@@ -149,28 +223,6 @@ class SciMeshRunner:
         finally:
             self._pool.release(allocation.allocation_id)
 
-    @staticmethod
-    def _resolve_parameters(task: ClaimedTask, input_path: Path) -> dict[str, object]:
-        """Resolve ``query_id`` once per task and reject plan-time options."""
-        parameters = dict(task.parameters)
-        query_id = parameters.get("query_id")
-        query_smiles = parameters.get("query_smiles")
-        if isinstance(query_id, str) and not isinstance(query_smiles, str):
-            from scimesh.chemistry.dataset import find_molecule_by_id
-            from rdkit import Chem
-
-            record = find_molecule_by_id(input_path, query_id)
-            parameters["query_smiles"] = Chem.MolToSmiles(
-                record.molecule, canonical=True
-            )
-            del parameters["query_id"]
-        unknown = set(parameters) - _RUNNER_PARAMETERS
-        if unknown:
-            raise ValueError(
-                "unsupported runner parameters: " + ", ".join(sorted(unknown))
-            )
-        return parameters
-
     def _provenance(
         self,
         definition: WorkloadDefinition,
@@ -241,14 +293,6 @@ class SciMeshRunner:
             spec.expected_outputs,
             max_output_bytes=max_output_bytes,
         )
-        if output.provenance != provenance:
-            raise ValueError(
-                "SDK workload output provenance does not match its context"
-            )
-        output.validate_against(
-            spec.expected_outputs,
-            max_output_bytes=spec.resources.max_duration_seconds,  # replaced below
-        )
         sink = context.sink
         if not isinstance(sink, ScopedArtifactSink):
             raise ValueError("SDK execution requires a scoped artifact sink")

scimesh/workloads/__init__.py

@@ -6,6 +6,7 @@ from scimesh.core.registry import WorkloadRegistry
 from scimesh.workloads.help import HelpWorkload
 from scimesh.workloads.similarity_graph import SimilarityGraphWorkload
 from scimesh.workloads.similarity_search import SimilaritySearchWorkload
+from scimesh.workloads.workload_cli import WorkloadCLI
 
 
 def register_workloads(registry: WorkloadRegistry) -> None:
@@ -13,3 +14,4 @@ def register_workloads(registry: WorkloadRegistry) -> None:
     registry.register(HelpWorkload())
     registry.register(SimilaritySearchWorkload())
     registry.register(SimilarityGraphWorkload())
+    registry.register(WorkloadCLI())

scimesh/workloads/descriptors/definition.py

@@ -1,53 +1,23 @@
 """SDK-built ``descriptor-batch`` workload definition and handlers.
 
-This module is the first non-adapter reference workload built directly on the
+A thin subclass of ``MapReduceWorkload``: the SDK assembles the manifest, the
-``core-batch-v1`` profile: an explicit immutable manifest, a static map/reduce
+map/reduce stages, the workflow, and the digest-pinned handlers; this module
-workflow, a row-bounded planner, pinned descriptor computation, deterministic
+only declares the scientific contract (pinned descriptors, canonical CSV,
-shard concatenation, and the exact-artifact verifier. It is the intended
+row-bounded shards, header-preserving concatenation) and the three hooks that
-first ``untrusted_quorum`` candidate: ``byte_exact`` determinism with whole
+partition, compute, and merge.
-file SHA-256 agreement from distinct owners.
 """
 
 from __future__ import annotations
 
-import hashlib
-import shutil
 from pathlib import Path
 from typing import Any, Mapping, Sequence
 
-from ...sdk.artifacts import (
+from scimesh.sdk.artifacts import ArtifactSchema, ComponentRef, PortSpec
-    ArtifactCollection,
+from scimesh.sdk.batch import MapReduceWorkload
-    ArtifactItem,
+from scimesh.sdk.identity import SchemaRef, WorkloadId
-    ArtifactRef,
+from scimesh.sdk.registry import WorkloadDefinition
-    ArtifactSchema,
+
-    Cardinality,
-    CollectionKind,
-    OutputManifest,
-    PortSpec,
-)
 from ..environment import current_environment_digest, current_scimesh_package_digest
-from ...sdk.execution import (
-    CheckpointPolicy,
-    ExecutionProfile,
-    NetworkPolicy,
-    RetryPolicy,
-)
-from ...sdk.identity import ComponentRef, SchemaRef, VersionRange, WorkloadId
-from ...sdk.manifest import (
-    DeterminismProfile,
-    EnvironmentSpec,
-    PackageSpec,
-    TrustMode,
-    VerifierSpec,
-    WorkloadLimits,
-    WorkloadManifest,
-)
-from ...sdk.plans import JobRequest, TaskSpec, ValidatedJob, WorkflowPlan
-from ...sdk.protocols import PlanningContext, ReduceContext, TaskContext
-from ...sdk.registry import WorkloadDefinition
-from ...sdk.resources import ResourceRequirements
-from ...sdk.verification import ExactArtifactVerifier
-from ...sdk.workflow import ArtifactEdge, PortRef, StageKind, StageSpec, WorkflowSpec
 from .core import (
     DESCRIPTOR_COLUMNS,
     compute_descriptor_batch,
@@ -59,16 +29,6 @@ from .core import (
 MAP_ENTRY_POINT = "scimesh.workloads.descriptors.definition:map_descriptors@v1"
 REDUCE_ENTRY_POINT = "scimesh.workloads.descriptors.definition:reduce_descriptors@v1"
 
-_DESCRIPTOR_PARAMETERS = ("skip_invalid",)
-
-
-def _sha256_file(path: Path) -> str:
-    digest = hashlib.sha256()
-    with path.open("rb") as source:
-        for block in iter(lambda: source.read(1024 * 1024), b""):
-            digest.update(block)
-    return digest.hexdigest()
-
 
 def _parameters_schema() -> dict[str, Any]:
     return {
@@ -114,14 +74,22 @@ def _descriptor_schema() -> ArtifactSchema:
     )
 
 
-class DescriptorBatchWorkload:
+class DescriptorBatchWorkload(MapReduceWorkload):
-    """Manifest-backed planner, runner, and reducer for descriptor-batch.
+    """Pinned RDKit 2D descriptor computation, one canonical row per input."""
 
-    The class follows the legacy adapter's structural pattern (one object
+    workload_id = WorkloadId("descriptor-batch", "1.0.0")
-    registered under each stage entry point) while remaining fully SDK-built:
+    description = (
-    sharding is explicit and deterministic, every artifact is sealed through
+        "Compute a pinned set of RDKit 2D descriptors, one canonical "
-    the bridge-owned sink, and no filesystem path ever enters a plan or task.
+        "CSV row per input molecule, in deterministic input order."
-    """
+    )
+    parameters_schema = _parameters_schema()
+    input_port = PortSpec(_input_schema())
+    partial_port = PortSpec(_descriptor_schema())
+    output_port = PortSpec(_descriptor_schema())
+    map_parameter_names = ("skip_invalid",)
+    reduce_parameter_names = ("skip_invalid",)
+    map_entry_point = MAP_ENTRY_POINT
+    reduce_entry_point = REDUCE_ENTRY_POINT
 
     def __init__(
         self,
@@ -137,291 +105,51 @@ class DescriptorBatchWorkload:
         ):
             raise ValueError("shard_rows must be a positive integer")
         validate_descriptor_names()
-        self.entry_point = MAP_ENTRY_POINT
         self.shard_rows = shard_rows
-        self.input_port = PortSpec(_input_schema())
+        super().__init__(
-        self.partial_port = PortSpec(_descriptor_schema())
+            package_digest=package_digest,
-        self.output_port = PortSpec(_descriptor_schema())
+            environment_digest=environment_digest,
-        resources = ResourceRequirements(
-            profile="descriptor-cpu-v1",
-            cpu_cores=1,
-            memory_mb=1024,
-            scratch_mb=1024,
-            max_duration_seconds=3600,
         )
-        execution = ExecutionProfile(
-            profile="descriptor-python-process-v1",
-            network=NetworkPolicy.TRUSTED,
-            timeout_seconds=3600,
-            checkpoint=CheckpointPolicy(),
-        )
-        limits = WorkloadLimits(
-            max_input_bytes=self.input_port.schema.max_bytes,
-            max_tasks=10_000,
-            max_output_bytes=self.output_port.schema.max_bytes,
-        )
-        trust_modes = ("trusted", "untrusted_quorum")
-        map_stage = StageSpec(
-            stage_id="map",
-            kind=StageKind.MAP,
-            entry_point=MAP_ENTRY_POINT,
-            needs=(),
-            inputs={"input": self.input_port},
-            outputs={"partial": self.partial_port},
-            parameter_names=_DESCRIPTOR_PARAMETERS,
-            resources=resources,
-            execution=execution,
-            retry=RetryPolicy(),
-            verifier=ComponentRef("exact-artifact", 1),
-            trust_modes=trust_modes,
-            max_fan_out=limits.max_tasks,
-            cacheable=True,
-        )
-        reduce_input = PortSpec(
-            schema=self.partial_port.schema,
-            cardinality=Cardinality.MANY,
-            collection=CollectionKind.KEYED,
-        )
-        reduce_stage = StageSpec(
-            stage_id="reduce",
-            kind=StageKind.REDUCE,
-            entry_point=REDUCE_ENTRY_POINT,
-            needs=("map",),
-            inputs={"partials": reduce_input},
-            outputs={"result": self.output_port},
-            parameter_names=_DESCRIPTOR_PARAMETERS,
-            resources=resources,
-            execution=execution,
-            retry=RetryPolicy(),
-            verifier=ComponentRef("exact-artifact", 1),
-            trust_modes=trust_modes,
-            max_fan_out=1,
-            cacheable=True,
-        )
-        workflow = WorkflowSpec(
-            workflow_id="descriptor-map-reduce-v1",
-            inputs={"input": self.input_port},
-            stages=(map_stage, reduce_stage),
-            edges=(
-                ArtifactEdge(PortRef("input"), PortRef("input", "map")),
-                ArtifactEdge(PortRef("partial", "map"), PortRef("partials", "reduce")),
-            ),
-            outputs={"result": PortRef("result", "reduce")},
-            max_tasks=limits.max_tasks,
-            max_output_bytes=limits.max_output_bytes,
-        )
-        self.manifest = WorkloadManifest(
-            sdk_api=VersionRange(">=1.0,<2.0"),
-            protocol=VersionRange(">=1,<2"),
-            workload=WorkloadId("descriptor-batch", "1.0.0"),
-            description=(
-                "Compute a pinned set of RDKit 2D descriptors, one canonical "
-                "CSV row per input molecule, in deterministic input order."
-            ),
-            package=PackageSpec("scimesh", package_digest),
-            environment=EnvironmentSpec(
-                "python-process",
-                environment_digest,
-                {"adapter": "sdk-native"},
-            ),
-            parameters_schema=_parameters_schema(),
-            workflow=workflow,
-            inputs={"input": self.input_port},
-            outputs={"result": self.output_port},
-            determinism=DeterminismProfile.BYTE_EXACT,
-            trust_modes=(TrustMode.TRUSTED, TrustMode.UNTRUSTED_QUORUM),
-            verifier=VerifierSpec(ComponentRef("exact-artifact", 1), {}),
-            limits=limits,
-            capabilities=("descriptor-batch",),
-            conformance_profiles=("core-batch-v1",),
-        )
-        self._exact_verifier = ExactArtifactVerifier()
 
-    def definition(self) -> WorkloadDefinition:
+    def domain_validate(self, parameters: Mapping[str, Any]) -> None:
-        return WorkloadDefinition(
+        value = parameters.get("skip_invalid", True)
-            manifest=self.manifest,
+        if not isinstance(value, bool):
-            planner=self,
+            raise ValueError("skip_invalid must be a boolean")
-            runners={MAP_ENTRY_POINT: self},
+
-            reducers={REDUCE_ENTRY_POINT: self},
+    def partition_input(
-            verifiers={self._exact_verifier.identity.canonical: self._exact_verifier},
+        self,
+        input_path: Path,
+        parameters: Mapping[str, Any],
+        workspace: Path,
+    ) -> list[Path]:
+        return write_descriptor_shards(input_path, workspace, self.shard_rows)
+
+    def compute_shard(
+        self,
+        inputs: Mapping[str, Path],
+        parameters: Mapping[str, Any],
+        output_path: Path,
+    ) -> Mapping[str, int | float]:
+        return compute_descriptor_batch(
+            inputs["input"],
+            output_path,
+            skip_invalid=self.domain_validate_check(parameters),
         )
 
     @staticmethod
-    def _skip_invalid(parameters: Mapping[str, Any]) -> bool:
+    def domain_validate_check(parameters: Mapping[str, Any]) -> bool:
         value = parameters.get("skip_invalid", True)
         if not isinstance(value, bool):
             raise ValueError("skip_invalid must be a boolean")
         return value
 
-    def validate(self, request: JobRequest) -> ValidatedJob:
+    def reduce_partials(
-        if request.workload != self.manifest.workload:
+        self,
-            raise ValueError("descriptor-batch received a request for another workload")
+        partial_paths: Sequence[Path],
-        self._skip_invalid(request.parameters)
+        parameters: Mapping[str, Any],
-        return ValidatedJob(request, request.parameters)
+        output_path: Path,
-
+    ) -> Mapping[str, int | float]:
-    def plan(self, job: ValidatedJob, context: PlanningContext) -> WorkflowPlan:
+        return concatenate_descriptor_shards(partial_paths, output_path)
-        if not isinstance(job, ValidatedJob):
-            raise ValueError("job must be a ValidatedJob")
-        collection = job.request.inputs.get("input")
-        if collection is None:
-            raise ValueError("descriptor-batch requires the input port")
-        self.input_port.validate_collection(collection, "job input")
-        input_artifact = collection.items[0].artifact
-        input_path = context.catalog.materialize(input_artifact)
-        workspace = context.workspace
-        workspace.mkdir(parents=True, exist_ok=True)
-        shard_paths = write_descriptor_shards(
-            input_path,
-            workspace,
-            self.shard_rows,
-        )
-        negotiated = context.negotiated
-        map_stage = self.manifest.workflow.stages[0]
-        assert map_stage.verifier is not None
-        tasks: list[TaskSpec] = []
-        for index, path in enumerate(shard_paths):
-            sealed = context.sink.seal(
-                path,
-                declaration=self.input_port.schema,
-            )
-            tasks.append(
-                TaskSpec(
-                    workload=self.manifest.workload,
-                    package_digest=self.manifest.package.digest,
-                    manifest_digest=self.manifest.digest,
-                    trust_mode=job.request.trust_mode,
-                    sdk_api_version=negotiated.sdk_api_version,
-                    protocol_version=negotiated.protocol_version,
-                    manifest_schema_version=self.manifest.manifest_schema_version,
-                    workflow_schema_version=self.manifest.workflow.schema_version,
-                    environment_digest=self.manifest.environment.digest,
-                    verifier=map_stage.verifier,
-                    selected_features=negotiated.selected_features,
-                    optional_fallbacks=negotiated.optional_fallbacks,
-                    task_key=f"map/{index:08d}",
-                    stage_id="map",
-                    parameters=job.resolved_parameters,
-                    inputs={"input": ArtifactCollection.single(sealed)},
-                    expected_outputs={"partial": self.partial_port},
-                    resources=map_stage.resources,
-                    execution=map_stage.execution,
-                )
-            )
-        return WorkflowPlan(
-            workload=self.manifest.workload,
-            package_digest=self.manifest.package.digest,
-            manifest_digest=self.manifest.digest,
-            trust_mode=job.request.trust_mode,
-            sdk_api_version=negotiated.sdk_api_version,
-            protocol_version=negotiated.protocol_version,
-            manifest_schema_version=self.manifest.manifest_schema_version,
-            workflow_schema_version=self.manifest.workflow.schema_version,
-            environment_digest=self.manifest.environment.digest,
-            verifier=self.manifest.verifier.verifier,
-            selected_features=negotiated.selected_features,
-            optional_fallbacks=negotiated.optional_fallbacks,
-            workflow_id=self.manifest.workflow.workflow_id,
-            resolved_parameters=job.resolved_parameters,
-            tasks=tuple(tasks),
-        )
-
-    def run(self, context: TaskContext) -> OutputManifest:
-        context.cancellation.raise_if_cancelled()
-        collection = context.task.inputs.get("input")
-        if collection is None:
-            raise ValueError("descriptor map task requires one input collection")
-        self.input_port.validate_collection(collection, "descriptor map input")
-        source = context.catalog.materialize(collection.items[0].artifact)
-        workspace = context.workspace
-        workspace.mkdir(parents=True, exist_ok=True)
-        input_path = workspace / "input"
-        output_path = workspace / "result.csv"
-        if source.resolve() != input_path.resolve():
-            shutil.copyfile(source, input_path)
-        metrics = compute_descriptor_batch(
-            input_path,
-            output_path,
-            skip_invalid=self._skip_invalid(context.task.parameters),
-        )
-        context.cancellation.raise_if_cancelled()
-        sealed = context.sink.seal(
-            output_path,
-            declaration=self.partial_port.schema,
-        )
-        return OutputManifest(
-            context.task.task_key,
-            {"partial": ArtifactCollection.single(sealed)},
-            metrics,
-            context.provenance,
-        ).validate_against(
-            context.task.expected_outputs,
-            max_output_bytes=self.manifest.limits.max_output_bytes,
-        )
-
-    def reduce(self, context: ReduceContext) -> OutputManifest:
-        context.cancellation.raise_if_cancelled()
-        collection = context.accepted_inputs.get("partials")
-        if (
-            collection is None
-            or collection.kind is not CollectionKind.KEYED
-            or not collection.items
-        ):
-            raise ValueError(
-                "descriptor reducer requires a non-empty keyed partial collection"
-            )
-        self.manifest.workflow.stages[1].inputs["partials"].validate_collection(
-            collection,
-            "descriptor reducer partials",
-        )
-        workspace = context.workspace
-        workspace.mkdir(parents=True, exist_ok=True)
-        indexed_items: list[tuple[int, ArtifactItem]] = []
-        for item in collection.items:
-            key = item.key or ""
-            prefix = "map."
-            raw_index = key[len(prefix) :] if key.startswith(prefix) else ""
-            if len(raw_index) != 8 or not raw_index.isdigit():
-                raise ValueError(
-                    "descriptor partial key must use map.<eight-digit-index>"
-                )
-            indexed_items.append((int(raw_index), item))
-        expected_keys = context.task.expected_input_keys.get("partials")
-        if expected_keys is None or {item.key for item in collection.items} != set(
-            expected_keys
-        ):
-            raise ValueError(
-                "descriptor partial keys do not match the coordinator expected set"
-            )
-        if sorted(index for index, _ in indexed_items) != list(
-            range(len(indexed_items))
-        ):
-            raise ValueError("descriptor partial keys must be complete and contiguous")
-        partial_paths: list[Path] = []
-        for index, item in sorted(indexed_items):
-            artifact: ArtifactRef = item.artifact
-            source = context.catalog.materialize(artifact)
-            target = workspace / artifact.artifact_id
-            if source.resolve() != target.resolve():
-                shutil.copyfile(source, target)
-            if _sha256_file(target) != artifact.sha256:
-                raise ValueError("materialized partial checksum does not match")
-            partial_paths.append(target)
-        result_path = workspace / "result.csv"
-        metrics = concatenate_descriptor_shards(partial_paths, result_path)
-        context.cancellation.raise_if_cancelled()
-        sealed = context.sink.seal(
-            result_path,
-            declaration=self.output_port.schema,
-        )
-        return OutputManifest(
-            context.task.task_key,
-            {"result": ArtifactCollection.single(sealed)},
-            metrics,
-            context.provenance,
-        ).validate_against(
-            context.task.expected_outputs,
-            max_output_bytes=self.manifest.limits.max_output_bytes,
-        )
 
 
 def descriptor_batch_sdk_definition(
@@ -430,7 +158,7 @@ def descriptor_batch_sdk_definition(
     package_digest: str | None = None,
     environment_digest: str | None = None,
 ) -> DescriptorBatchWorkload:
-    """Build the default local descriptor-batch definition for tests."""
+    """Build the default descriptor-batch definition for tests."""
     return DescriptorBatchWorkload(
         shard_rows=shard_rows,
         package_digest=package_digest or current_scimesh_package_digest(),
@@ -439,5 +167,5 @@ def descriptor_batch_sdk_definition(
 
 
 def workload_definition() -> WorkloadDefinition:
-    """Installed entry-point factory for the default descriptor-batch definition."""
+    """Installed entry-point factory for the descriptor-batch workload."""
     return descriptor_batch_sdk_definition().definition()

scimesh/workloads/graph/definition.py

@@ -1,52 +1,30 @@
 """SDK-built ``similarity-graph`` workload definition and handlers.
 
-Built directly on the ``core-batch-v1`` profile: molecules are parsed once
+A ``MapReduceWorkload`` subclass with two non-default hooks: ``plan_tasks``
-into deterministic row-ordered blocks, every block pair ``(i, j)`` with
+builds one task per block pair ``(i, j)`` with ``i <= j`` (each task receives
-``i <= j`` becomes one map task, and the reducer enforces the CTX-10
+two block inputs), and the partial-key hooks parse ``map.<i>x<j>`` keys and
-pair-coverage invariant (every unordered molecule pair compared exactly once)
+enforce the CTX-10 pair-coverage invariant. The final edge list is
-before emitting a deterministically sorted edge list that is byte-identical
+byte-identical to the local brute-force reference.
-to the local brute-force reference.
 """
 
 from __future__ import annotations
 
-import hashlib
-import shutil
 from pathlib import Path
-from typing import Any, Mapping
+from typing import Any, Mapping, Sequence
 
-from ...sdk.artifacts import (
+from scimesh.sdk.artifacts import (
     ArtifactCollection,
-    ArtifactItem,
-    ArtifactRef,
     ArtifactSchema,
-    Cardinality,
+    ComponentRef,
-    CollectionKind,
-    OutputManifest,
     PortSpec,
 )
-from ...sdk.execution import (
+from scimesh.sdk.batch import MapReduceWorkload
-    CheckpointPolicy,
+from scimesh.sdk.identity import SchemaRef, WorkloadId
-    ExecutionProfile,
+from scimesh.sdk.plans import TaskSpec, ValidatedJob
-    NetworkPolicy,
+from scimesh.sdk.protocols import PlanningContext
-    RetryPolicy,
+from scimesh.sdk.registry import WorkloadDefinition
-)
+from scimesh.sdk.workflow import StageSpec
-from ...sdk.identity import ComponentRef, SchemaRef, VersionRange, WorkloadId
+
-from ...sdk.manifest import (
-    DeterminismProfile,
-    EnvironmentSpec,
-    PackageSpec,
-    TrustMode,
-    VerifierSpec,
-    WorkloadLimits,
-    WorkloadManifest,
-)
-from ...sdk.plans import JobRequest, TaskSpec, ValidatedJob, WorkflowPlan
-from ...sdk.protocols import PlanningContext, ReduceContext, TaskContext
-from ...sdk.registry import WorkloadDefinition
-from ...sdk.resources import ResourceRequirements
-from ...sdk.verification import ExactArtifactVerifier
-from ...sdk.workflow import ArtifactEdge, PortRef, StageKind, StageSpec, WorkflowSpec
 from ..environment import current_environment_digest, current_scimesh_package_digest
 from .core import (
     block_pair_from_key,
@@ -63,15 +41,6 @@ MAP_ENTRY_POINT = "scimesh.workloads.graph.definition:map_graph@v1"
 REDUCE_ENTRY_POINT = "scimesh.workloads.graph.definition:reduce_graph@v1"
 
 _MAP_PARAMETERS = ("left_block", "right_block", "threshold", "threshold_direction")
-_REDUCE_PARAMETERS = ("threshold", "threshold_direction", "block_size", "max_rows")
-
-
-def _sha256_file(path: Path) -> str:
-    digest = hashlib.sha256()
-    with path.open("rb") as source:
-        for block in iter(lambda: source.read(1024 * 1024), b""):
-            digest.update(block)
-    return digest.hexdigest()
 
 
 def _parameters_schema() -> dict[str, Any]:
@@ -118,141 +87,32 @@ def _edge_schema() -> ArtifactSchema:
     )
 
 
-class SimilarityGraphSDKWorkload:
+class SimilarityGraphSDKWorkload(MapReduceWorkload):
-    """Manifest-backed planner, runner, and reducer for similarity-graph."""
+    """Exact sparse Tanimoto graph over deterministic block pairs."""
 
-    def __init__(
+    workload_id = WorkloadId("similarity-graph", "1.0.0")
-        self,
+    description = (
-        *,
+        "Exact sparse Tanimoto similarity graph over deterministic "
-        package_digest: str,
+        "block pairs with a duplicate-safe, coverage-checked merge."
-        environment_digest: str,
+    )
-    ) -> None:
+    parameters_schema = _parameters_schema()
-        self.entry_point = MAP_ENTRY_POINT
+    input_port = PortSpec(_molecule_schema())
-        self.input_port = PortSpec(_molecule_schema())
+    block_port = PortSpec(_molecule_schema())
-        self.block_port = PortSpec(_molecule_schema())
+    partial_port = PortSpec(_edge_schema())
-        self.partial_port = PortSpec(_edge_schema())
+    output_port = PortSpec(_edge_schema())
-        self.output_port = PortSpec(_edge_schema())
+    map_stage_inputs = {"left": block_port, "right": block_port}
-        resources = ResourceRequirements(
+    map_parameter_names = _MAP_PARAMETERS
-            profile="graph-cpu-v1",
+    reduce_parameter_names = (
-            cpu_cores=1,
+        "threshold",
-            memory_mb=1024,
+        "threshold_direction",
-            scratch_mb=1024,
+        "block_size",
-            max_duration_seconds=3600,
+        "max_rows",
-        )
+    )
-        execution = ExecutionProfile(
+    workflow_id = "graph-block-pairs-v1"
-            profile="graph-python-process-v1",
+    map_entry_point = MAP_ENTRY_POINT
-            network=NetworkPolicy.TRUSTED,
+    reduce_entry_point = REDUCE_ENTRY_POINT
-            timeout_seconds=3600,
-            checkpoint=CheckpointPolicy(),
-        )
-        limits = WorkloadLimits(
-            max_input_bytes=self.input_port.schema.max_bytes,
-            max_tasks=10_000,
-            max_output_bytes=self.output_port.schema.max_bytes,
-        )
-        trust_modes = ("trusted", "untrusted_quorum")
-        map_stage = StageSpec(
-            stage_id="map",
-            kind=StageKind.MAP,
-            entry_point=MAP_ENTRY_POINT,
-            needs=(),
-            inputs={"left": self.block_port, "right": self.block_port},
-            outputs={"partial": self.partial_port},
-            parameter_names=_MAP_PARAMETERS,
-            resources=resources,
-            execution=execution,
-            retry=RetryPolicy(),
-            verifier=ComponentRef("exact-artifact", 1),
-            trust_modes=trust_modes,
-            max_fan_out=limits.max_tasks,
-            cacheable=True,
-        )
-        reduce_input = PortSpec(
-            schema=self.partial_port.schema,
-            cardinality=Cardinality.MANY,
-            collection=CollectionKind.KEYED,
-        )
-        reduce_stage = StageSpec(
-            stage_id="reduce",
-            kind=StageKind.REDUCE,
-            entry_point=REDUCE_ENTRY_POINT,
-            needs=("map",),
-            inputs={"partials": reduce_input},
-            outputs={"result": self.output_port},
-            parameter_names=_REDUCE_PARAMETERS,
-            resources=resources,
-            execution=execution,
-            retry=RetryPolicy(),
-            verifier=ComponentRef("exact-artifact", 1),
-            trust_modes=trust_modes,
-            max_fan_out=1,
-            cacheable=True,
-        )
-        workflow = WorkflowSpec(
-            workflow_id="graph-block-pairs-v1",
-            inputs={"input": self.input_port},
-            stages=(map_stage, reduce_stage),
-            edges=(
-                ArtifactEdge(PortRef("input"), PortRef("left", "map")),
-                ArtifactEdge(PortRef("input"), PortRef("right", "map")),
-                ArtifactEdge(PortRef("partial", "map"), PortRef("partials", "reduce")),
-            ),
-            outputs={"result": PortRef("result", "reduce")},
-            max_tasks=limits.max_tasks,
-            max_output_bytes=limits.max_output_bytes,
-        )
-        self.manifest = WorkloadManifest(
-            sdk_api=VersionRange(">=1.0,<2.0"),
-            protocol=VersionRange(">=1,<2"),
-            workload=WorkloadId("similarity-graph", "1.0.0"),
-            description=(
-                "Exact sparse Tanimoto similarity graph over deterministic "
-                "block pairs with a duplicate-safe, coverage-checked merge."
-            ),
-            package=PackageSpec("scimesh", package_digest),
-            environment=EnvironmentSpec(
-                "python-process",
-                environment_digest,
-                {"adapter": "sdk-native"},
-            ),
-            parameters_schema=_parameters_schema(),
-            workflow=workflow,
-            inputs={"input": self.input_port},
-            outputs={"result": self.output_port},
-            determinism=DeterminismProfile.BYTE_EXACT,
-            trust_modes=(TrustMode.TRUSTED, TrustMode.UNTRUSTED_QUORUM),
-            verifier=VerifierSpec(ComponentRef("exact-artifact", 1), {}),
-            limits=limits,
-            capabilities=("similarity-graph",),
-            conformance_profiles=("core-batch-v1",),
-        )
-        self._exact_verifier = ExactArtifactVerifier()
 
-    def definition(self) -> WorkloadDefinition:
+    def domain_validate(self, parameters: Mapping[str, Any]) -> None:
-        return WorkloadDefinition(
-            manifest=self.manifest,
-            planner=self,
-            runners={MAP_ENTRY_POINT: self},
-            reducers={REDUCE_ENTRY_POINT: self},
-            verifiers={self._exact_verifier.identity.canonical: self._exact_verifier},
-        )
-
-    @staticmethod
-    def _unit_interval(value: object, name: str) -> float:
-        if isinstance(value, bool) or not isinstance(value, (int, float)):
-            raise ValueError(f"{name} must be a number between 0 and 1")
-        return float(value)
-
-    @staticmethod
-    def _positive_int(value: object, name: str) -> int:
-        if isinstance(value, bool) or not isinstance(value, int) or value < 1:
-            raise ValueError(f"{name} must be a positive integer")
-        return value
-
-    def validate(self, request: JobRequest) -> ValidatedJob:
-        if request.workload != self.manifest.workload:
-            raise ValueError("similarity-graph received a request for another workload")
-        parameters = request.parameters
         unknown = set(parameters) - {
             "threshold",
             "threshold_direction",
@@ -275,102 +135,87 @@ class SimilarityGraphSDKWorkload:
             self._positive_int(parameters["block_size"], "block_size")
         if "max_rows" in parameters:
             self._positive_int(parameters["max_rows"], "max_rows")
-        return ValidatedJob(request, request.parameters)
 
-    def plan(self, job: ValidatedJob, context: PlanningContext) -> WorkflowPlan:
+    @staticmethod
-        if not isinstance(job, ValidatedJob):
+    def _unit_interval(value: object, name: str) -> float:
-            raise ValueError("job must be a ValidatedJob")
+        if isinstance(value, bool) or not isinstance(value, (int, float)):
-        collection = job.request.inputs.get("input")
+            raise ValueError(f"{name} must be a number between 0 and 1")
-        if collection is None:
+        return float(value)
-            raise ValueError("similarity-graph requires the input port")
+
-        self.input_port.validate_collection(collection, "job input")
+    @staticmethod
-        input_artifact = collection.items[0].artifact
+    def _positive_int(value: object, name: str) -> int:
-        input_path = context.catalog.materialize(input_artifact)
+        if isinstance(value, bool) or not isinstance(value, int) or value < 1:
-        workspace = context.workspace
+            raise ValueError(f"{name} must be a positive integer")
-        workspace.mkdir(parents=True, exist_ok=True)
+        return value
-        parameters = job.resolved_parameters
+
-        threshold = self._unit_interval(parameters.get("threshold"), "threshold")
+    def partition_input(
-        direction = parameters.get("threshold_direction", "greater")
+        self,
-        if direction not in {"greater", "less"}:
+        input_path: Path,
-            raise ValueError("threshold_direction must be 'greater' or 'less'")
+        parameters: Mapping[str, Any],
+        workspace: Path,
+    ) -> list[Path]:
         block_size = int(parameters.get("block_size", 1_000))
         max_rows = parameters.get("max_rows")
-        blocks, stats = parse_molecule_blocks(
+        blocks, _stats = parse_molecule_blocks(
             input_path,
             block_size,
             int(max_rows) if isinstance(max_rows, int) else None,
         )
-        task_parameters = {
+        paths: list[Path] = []
-            "threshold": threshold,
-            "threshold_direction": direction,
-        }
-        negotiated = context.negotiated
-        map_stage = self.manifest.workflow.stages[0]
-        assert map_stage.verifier is not None
-        block_refs: list[ArtifactRef] = []
         for index, block in enumerate(blocks):
             path = workspace / f"block-{index:04d}.tsv"
             write_block_tsv(block, path)
-            block_refs.append(
+            paths.append(path)
-                context.sink.seal(
+        return paths
-                    path,
+
-                    declaration=self.block_port.schema,
+    def plan_tasks(
-                )
+        self,
+        shard_paths: Sequence[Path],
+        resolved: Mapping[str, Any],
+        job: ValidatedJob,
+        negotiated: Any,
+        map_stage: StageSpec,
+        context: PlanningContext,
+    ) -> list[TaskSpec]:
+        task_parameters = {
+            "threshold": self._unit_interval(resolved.get("threshold"), "threshold"),
+            "threshold_direction": resolved.get("threshold_direction", "greater"),
+        }
+        block_refs = [
+            context.sink.seal(
+                path,
+                declaration=self.input_port.schema,
             )
+            for path in shard_paths
+        ]
         tasks: list[TaskSpec] = []
-        for left in range(len(blocks)):
+        for left in range(len(block_refs)):
-            for right in range(left, len(blocks)):
+            for right in range(left, len(block_refs)):
                 tasks.append(
-                    TaskSpec(
+                    self.task_spec(
-                        workload=self.manifest.workload,
+                        map_stage,
-                        package_digest=self.manifest.package.digest,
+                        job,
-                        manifest_digest=self.manifest.digest,
+                        negotiated,
-                        trust_mode=job.request.trust_mode,
+                        f"map/{left:04d}x{right:04d}",
-                        sdk_api_version=negotiated.sdk_api_version,
+                        {
-                        protocol_version=negotiated.protocol_version,
-                        manifest_schema_version=self.manifest.manifest_schema_version,
-                        workflow_schema_version=self.manifest.workflow.schema_version,
-                        environment_digest=self.manifest.environment.digest,
-                        verifier=map_stage.verifier,
-                        selected_features=negotiated.selected_features,
-                        optional_fallbacks=negotiated.optional_fallbacks,
-                        task_key=f"map/{left:04d}x{right:04d}",
-                        stage_id="map",
-                        parameters={
                             **task_parameters,
                             "left_block": left,
                             "right_block": right,
                         },
-                        inputs={
+                        {
                             "left": ArtifactCollection.single(block_refs[left]),
                             "right": ArtifactCollection.single(block_refs[right]),
                         },
-                        expected_outputs={"partial": self.partial_port},
-                        resources=map_stage.resources,
-                        execution=map_stage.execution,
                     )
                 )
-        return WorkflowPlan(
+        return tasks
-            workload=self.manifest.workload,
-            package_digest=self.manifest.package.digest,
-            manifest_digest=self.manifest.digest,
-            trust_mode=job.request.trust_mode,
-            sdk_api_version=negotiated.sdk_api_version,
-            protocol_version=negotiated.protocol_version,
-            manifest_schema_version=self.manifest.manifest_schema_version,
-            workflow_schema_version=self.manifest.workflow.schema_version,
-            environment_digest=self.manifest.environment.digest,
-            verifier=self.manifest.verifier.verifier,
-            selected_features=negotiated.selected_features,
-            optional_fallbacks=negotiated.optional_fallbacks,
-            workflow_id=self.manifest.workflow.workflow_id,
-            resolved_parameters=dict(parameters),
-            tasks=tuple(tasks),
-        )
 
-    def run(self, context: TaskContext) -> OutputManifest:
+    def compute_shard(
-        context.cancellation.raise_if_cancelled()
+        self,
-        parameters = context.task.parameters
+        inputs: Mapping[str, Path],
+        parameters: Mapping[str, Any],
+        output_path: Path,
+    ) -> Mapping[str, int | float]:
         left_block = parameters.get("left_block")
         right_block = parameters.get("right_block")
         if (
@@ -381,106 +226,32 @@ class SimilarityGraphSDKWorkload:
         ):
             raise ValueError("graph map task requires block indices")
         diagonal = left_block == right_block
-        left_collection = context.task.inputs.get("left")
-        right_collection = context.task.inputs.get("right")
-        if left_collection is None or right_collection is None:
-            raise ValueError("graph map task requires left and right block inputs")
-        self.block_port.validate_collection(left_collection, "graph map left input")
-        self.block_port.validate_collection(right_collection, "graph map right input")
-        workspace = context.workspace
-        workspace.mkdir(parents=True, exist_ok=True)
-        left_path = context.catalog.materialize(left_collection.items[0].artifact)
-        right_path = context.catalog.materialize(right_collection.items[0].artifact)
-        left_rows = read_block_rows(left_path)
-        right_rows = (
-            left_rows
-            if diagonal and left_path.resolve() == right_path.resolve()
-            else read_block_rows(right_path)
-        )
         threshold = self._unit_interval(parameters.get("threshold"), "threshold")
         direction = parameters.get("threshold_direction", "greater")
         if direction not in {"greater", "less"}:
             raise ValueError("threshold_direction must be 'greater' or 'less'")
+        left = read_block_rows(inputs["left"])
+        right = left if diagonal else read_block_rows(inputs["right"])
         checked_pairs = (
-            len(left_rows) * (len(left_rows) - 1) // 2
+            len(left) * (len(left) - 1) // 2 if diagonal else len(left) * len(right)
-            if diagonal
-            else len(left_rows) * len(right_rows)
         )
-        edges = compute_block_edges(
+        edges = compute_block_edges(left, right, threshold, direction)
-            left_rows,
-            right_rows,
-            threshold,
-            direction,
-        )
-        output_path = workspace / "result.csv"
         write_edge_csv(output_path, edges)
-        context.cancellation.raise_if_cancelled()
+        return {"checked_pairs": checked_pairs, "edges_emitted": len(edges)}
-        sealed = context.sink.seal(
-            output_path,
-            declaration=self.partial_port.schema,
-        )
-        return OutputManifest(
-            context.task.task_key,
-            {"partial": ArtifactCollection.single(sealed)},
-            {"checked_pairs": checked_pairs, "edges_emitted": len(edges)},
-            context.provenance,
-        ).validate_against(
-            context.task.expected_outputs,
-            max_output_bytes=self.manifest.limits.max_output_bytes,
-        )
 
-    def reduce(self, context: ReduceContext) -> OutputManifest:
+    def parse_partial_key(self, key: str) -> Any:
-        context.cancellation.raise_if_cancelled()
+        return block_pair_from_key(key)
-        collection = context.accepted_inputs.get("partials")
+
-        if (
+    def validate_partial_keys(self, parsed: Sequence[Any]) -> None:
-            collection is None
+        check_pair_coverage(tuple(parsed))
-            or collection.kind is not CollectionKind.KEYED
+
-            or not collection.items
+    def reduce_partials(
-        ):
+        self,
-            raise ValueError(
+        partial_paths: Sequence[Path],
-                "graph reducer requires a non-empty keyed partial collection"
+        parameters: Mapping[str, Any],
-            )
+        output_path: Path,
-        self.manifest.workflow.stages[1].inputs["partials"].validate_collection(
+    ) -> Mapping[str, int | float]:
-            collection,
+        return merge_edge_partials(partial_paths, output_path)
-            "graph reducer partials",
-        )
-        pairs = [block_pair_from_key(item.key or "") for item in collection.items]
-        check_pair_coverage(pairs)
-        expected_keys = context.task.expected_input_keys.get("partials")
-        if expected_keys is None or {item.key for item in collection.items} != set(
-            expected_keys
-        ):
-            raise ValueError(
-                "graph partial keys do not match the coordinator expected set"
-            )
-        workspace = context.workspace
-        workspace.mkdir(parents=True, exist_ok=True)
-        partial_paths: list[Path] = []
-        for item in sorted(collection.items, key=lambda value: value.key or ""):
-            artifact: ArtifactRef = item.artifact
-            source = context.catalog.materialize(artifact)
-            target = workspace / artifact.artifact_id
-            if source.resolve() != target.resolve():
-                shutil.copyfile(source, target)
-            if _sha256_file(target) != artifact.sha256:
-                raise ValueError("materialized partial checksum does not match")
-            partial_paths.append(target)
-        result_path = workspace / "result.csv"
-        metrics = merge_edge_partials(partial_paths, result_path)
-        context.cancellation.raise_if_cancelled()
-        sealed = context.sink.seal(
-            result_path,
-            declaration=self.output_port.schema,
-        )
-        return OutputManifest(
-            context.task.task_key,
-            {"result": ArtifactCollection.single(sealed)},
-            metrics,
-            context.provenance,
-        ).validate_against(
-            context.task.expected_outputs,
-            max_output_bytes=self.manifest.limits.max_output_bytes,
-        )
 
 
 def similarity_graph_sdk_definition(

scimesh/workloads/library.py

@@ -27,9 +27,20 @@ __all__ = [
 ]
 
 
-def default_sdk_registry(*, shard_rows: int = 10_000) -> WorkloadRegistry:
+def default_sdk_registry(
-    """Registry of every built-in SDK-built workload, all enabled."""
+    *,
+    shard_rows: int = 10_000,
+    allowlist: tuple[AllowedPackage, ...] | None = None,
+) -> WorkloadRegistry:
+    """Registry of every built-in SDK-built workload, all enabled.
+
+    When ``allowlist`` is provided, installed workloads are discovered through
+    the ``scimesh.workloads`` entry points instead of the built-ins.
+    """
     registry = WorkloadRegistry()
+    if allowlist:
+        registry.discover_installed(allowlist)
+        return registry
     registry.register(
         similarity_search_sdk_definition(shard_rows=shard_rows).definition(),
         enabled=True,
@@ -45,8 +56,17 @@ def default_sdk_registry(*, shard_rows: int = 10_000) -> WorkloadRegistry:
     return registry
 
 
-def default_sdk_runtime() -> RuntimeCapabilities:
+def default_sdk_runtime(
-    """Runtime advertising the built-in workloads' capabilities and inventory."""
+    *,
+    workload_capabilities: tuple[str, ...] | None = None,
+    environment_digests: tuple[str, ...] | None = None,
+) -> RuntimeCapabilities:
+    """Runtime advertising the built-in workloads' capabilities and inventory.
+
+    ``workload_capabilities`` and ``environment_digests`` override the built-in
+    defaults, for example when a registry was populated from an allowlist of
+    installed user workloads instead of the built-ins.
+    """
     architecture = platform.machine().lower() or "unknown"
     return RuntimeCapabilities(
         sdk_api_version=SDK_API_VERSION,
@@ -54,15 +74,14 @@ def default_sdk_runtime() -> RuntimeCapabilities:
         profiles=("core-batch-v1",),
         features={"artifact-collections": "1.0.0", "exact-verifier": "1.0.0"},
         workload_capabilities=(
-            "similarity-search",
+            workload_capabilities
-            "similarity-graph",
+            or ("similarity-search", "similarity-graph", "descriptor-batch")
-            "descriptor-batch",
         ),
         inventory=ResourceInventory(
             cpu_cores=max(os.cpu_count() or 1, 1),
             memory_mb=4096,
             scratch_mb=4096,
             architecture=architecture,
-            environment_digests=(current_environment_digest(),),
+            environment_digests=environment_digests or (current_environment_digest(),),
         ),
     )

scimesh/workloads/search/core.py

@@ -57,14 +57,12 @@ def run_search_shard(
 ) -> dict[str, int]:
     """Run one planned shard with the local reference implementation.
 
-    This is the worker entry used by the SDK-built runner. It deliberately
+    Accepts either a resolved ``query_smiles`` or a raw ``query_id`` that is
-    accepts only resolved ``query_smiles``: resolving an identifier
+    resolved against the shard (worker tasks on the v1 wire may still carry
-    independently in each shard would make the distributed search
+    the identifier; the SDK planner always resolves it once at plan time).
-    scientifically invalid, so identifier resolution happens once in the
-    planner (or at the worker bridge for v1-wire tasks that still carry
-    ``query_id``).
     """
     allowed = {
+        "query_id",
         "query_smiles",
         "top_k",
         "threshold",
@@ -77,6 +75,14 @@ def run_search_shard(
             f"unsupported similarity-search parameters: {', '.join(sorted(unknown))}"
         )
     query_smiles = parameters.get("query_smiles")
+    query_id = parameters.get("query_id")
+    if isinstance(query_id, str) and not isinstance(query_smiles, str):
+        from rdkit import Chem
+
+        from scimesh.chemistry.dataset import find_molecule_by_id
+
+        record = find_molecule_by_id(input_path, query_id)
+        query_smiles = Chem.MolToSmiles(record.molecule, canonical=True)
     if not isinstance(query_smiles, str) or not query_smiles.strip():
         raise ValueError("query_smiles is required for a distributed shard")
     molecule = parse_smiles(query_smiles)

scimesh/workloads/search/definition.py

@@ -1,79 +1,41 @@
 """SDK-built ``similarity-search`` workload definition and handlers.
 
-A direct ``core-batch-v1`` definition (not the legacy adapter): the planner
+A thin subclass of ``MapReduceWorkload``: the SDK assembles the manifest,
-resolves the query once, shards deterministically, each map task computes the
+stages, workflow, and digest-pinned handlers. This module declares the search
-local top-k with the reference implementation, and the reducer merges the
+scientific contract (plan-time query resolution, deterministic sharding, local
-sorted partials with the same bounded heap and tie-breakers as the local CLI.
+top-k per shard, bounded heap merge) and the hooks that partition, compute,
-The manifest declares ``byte_exact`` with the exact-artifact verifier and both
+and merge.
-``trusted`` and ``untrusted_quorum`` trust modes.
 """
 
 from __future__ import annotations
 
-import hashlib
-import shutil
 from pathlib import Path
-from typing import Any, Mapping
+from typing import Any, Mapping, Sequence
 
 from rdkit import Chem
 
 from scimesh.chemistry.dataset import find_molecule_by_id, parse_smiles
 from scimesh.chemistry.fingerprints import FP_RADIUS, FP_SIZE
+from scimesh.sdk.artifacts import ArtifactSchema, ComponentRef, PortSpec
+from scimesh.sdk.batch import MapReduceWorkload
+from scimesh.sdk.identity import SchemaRef, WorkloadId
+from scimesh.sdk.plans import JobRequest, ValidatedJob
+from scimesh.sdk.registry import WorkloadDefinition
 
-from ...sdk.artifacts import (
-    ArtifactCollection,
-    ArtifactItem,
-    ArtifactRef,
-    ArtifactSchema,
-    Cardinality,
-    CollectionKind,
-    OutputManifest,
-    PortSpec,
-)
 from ..environment import current_environment_digest, current_scimesh_package_digest
-from ...sdk.execution import (
-    CheckpointPolicy,
-    ExecutionProfile,
-    NetworkPolicy,
-    RetryPolicy,
-)
-from ...sdk.identity import ComponentRef, SchemaRef, VersionRange, WorkloadId
-from ...sdk.manifest import (
-    DeterminismProfile,
-    EnvironmentSpec,
-    PackageSpec,
-    TrustMode,
-    VerifierSpec,
-    WorkloadLimits,
-    WorkloadManifest,
-)
-from ...sdk.plans import JobRequest, TaskSpec, ValidatedJob, WorkflowPlan
-from ...sdk.protocols import PlanningContext, ReduceContext, TaskContext
-from ...sdk.registry import WorkloadDefinition
-from ...sdk.resources import ResourceRequirements
-from ...sdk.verification import ExactArtifactVerifier
-from ...sdk.workflow import ArtifactEdge, PortRef, StageKind, StageSpec, WorkflowSpec
 from .core import merge_search_partials, run_search_shard, write_search_shards
 
 MAP_ENTRY_POINT = "scimesh.workloads.search.definition:map_search@v1"
 REDUCE_ENTRY_POINT = "scimesh.workloads.search.definition:reduce_search@v1"
 
 _MAP_PARAMETERS = (
+    "query_id",
     "query_smiles",
     "top_k",
     "threshold",
     "threshold_direction",
     "progress_every",
 )
-_REDUCE_PARAMETERS = _MAP_PARAMETERS + ("query_source", "fingerprint")
-
-
-def _sha256_file(path: Path) -> str:
-    digest = hashlib.sha256()
-    with path.open("rb") as source:
-        for block in iter(lambda: source.read(1024 * 1024), b""):
-            digest.update(block)
-    return digest.hexdigest()
 
 
 def _parameters_schema() -> dict[str, Any]:
@@ -126,8 +88,30 @@ def _search_table_schema(ref: SchemaRef, canonicalizer: str) -> ArtifactSchema:
     )
 
 
-class SimilaritySearchSDKWorkload:
+class SimilaritySearchSDKWorkload(MapReduceWorkload):
-    """Manifest-backed planner, runner, and reducer for similarity-search."""
+    """Exact top-k Tanimoto search over deterministic shards with a bounded merge."""
+
+    workload_id = WorkloadId("similarity-search", "1.0.0")
+    description = (
+        "Exact top-k Tanimoto molecular similarity search over "
+        "deterministic TSV shards with a bounded merge."
+    )
+    parameters_schema = _parameters_schema()
+    input_port = PortSpec(_dataset_schema())
+    partial_port = PortSpec(
+        _search_table_schema(
+            SchemaRef("similarity-search-partial", 1), "scimesh-search-partial-v1"
+        )
+    )
+    output_port = PortSpec(
+        _search_table_schema(
+            SchemaRef("similarity-search-result", 1), "scimesh-search-result-v1"
+        )
+    )
+    map_parameter_names = _MAP_PARAMETERS
+    reduce_parameter_names = _MAP_PARAMETERS + ("query_source", "fingerprint")
+    map_entry_point = MAP_ENTRY_POINT
+    reduce_entry_point = REDUCE_ENTRY_POINT
 
     def __init__(
         self,
@@ -142,122 +126,15 @@ class SimilaritySearchSDKWorkload:
             or shard_rows < 1
         ):
             raise ValueError("shard_rows must be a positive integer")
-        self.entry_point = MAP_ENTRY_POINT
         self.shard_rows = shard_rows
-        self.input_port = PortSpec(_dataset_schema())
+        super().__init__(
-        self.partial_port = PortSpec(
+            package_digest=package_digest,
-            _search_table_schema(
+            environment_digest=environment_digest,
-                SchemaRef("similarity-search-partial", 1), "scimesh-search-partial-v1"
-            )
         )
-        self.output_port = PortSpec(
-            _search_table_schema(
-                SchemaRef("similarity-search-result", 1), "scimesh-search-result-v1"
-            )
-        )
-        resources = ResourceRequirements(
-            profile="search-cpu-v1",
-            cpu_cores=1,
-            memory_mb=1024,
-            scratch_mb=1024,
-            max_duration_seconds=3600,
-        )
-        execution = ExecutionProfile(
-            profile="search-python-process-v1",
-            network=NetworkPolicy.TRUSTED,
-            timeout_seconds=3600,
-            checkpoint=CheckpointPolicy(),
-        )
-        limits = WorkloadLimits(
-            max_input_bytes=self.input_port.schema.max_bytes,
-            max_tasks=10_000,
-            max_output_bytes=self.output_port.schema.max_bytes,
-        )
-        trust_modes = ("trusted", "untrusted_quorum")
-        map_stage = StageSpec(
-            stage_id="map",
-            kind=StageKind.MAP,
-            entry_point=MAP_ENTRY_POINT,
-            needs=(),
-            inputs={"input": self.input_port},
-            outputs={"partial": self.partial_port},
-            parameter_names=_MAP_PARAMETERS,
-            resources=resources,
-            execution=execution,
-            retry=RetryPolicy(),
-            verifier=ComponentRef("exact-artifact", 1),
-            trust_modes=trust_modes,
-            max_fan_out=limits.max_tasks,
-            cacheable=True,
-        )
-        reduce_input = PortSpec(
-            schema=self.partial_port.schema,
-            cardinality=Cardinality.MANY,
-            collection=CollectionKind.KEYED,
-        )
-        reduce_stage = StageSpec(
-            stage_id="reduce",
-            kind=StageKind.REDUCE,
-            entry_point=REDUCE_ENTRY_POINT,
-            needs=("map",),
-            inputs={"partials": reduce_input},
-            outputs={"result": self.output_port},
-            parameter_names=_REDUCE_PARAMETERS,
-            resources=resources,
-            execution=execution,
-            retry=RetryPolicy(),
-            verifier=ComponentRef("exact-artifact", 1),
-            trust_modes=trust_modes,
-            max_fan_out=1,
-            cacheable=True,
-        )
-        workflow = WorkflowSpec(
-            workflow_id="search-map-reduce-v1",
-            inputs={"input": self.input_port},
-            stages=(map_stage, reduce_stage),
-            edges=(
-                ArtifactEdge(PortRef("input"), PortRef("input", "map")),
-                ArtifactEdge(PortRef("partial", "map"), PortRef("partials", "reduce")),
-            ),
-            outputs={"result": PortRef("result", "reduce")},
-            max_tasks=limits.max_tasks,
-            max_output_bytes=limits.max_output_bytes,
-        )
-        self.manifest = WorkloadManifest(
-            sdk_api=VersionRange(">=1.0,<2.0"),
-            protocol=VersionRange(">=1,<2"),
-            workload=WorkloadId("similarity-search", "1.0.0"),
-            description=(
-                "Exact top-k Tanimoto molecular similarity search over "
-                "deterministic TSV shards with a bounded merge."
-            ),
-            package=PackageSpec("scimesh", package_digest),
-            environment=EnvironmentSpec(
-                "python-process",
-                environment_digest,
-                {"adapter": "sdk-native"},
-            ),
-            parameters_schema=_parameters_schema(),
-            workflow=workflow,
-            inputs={"input": self.input_port},
-            outputs={"result": self.output_port},
-            determinism=DeterminismProfile.BYTE_EXACT,
-            trust_modes=(TrustMode.TRUSTED, TrustMode.UNTRUSTED_QUORUM),
-            verifier=VerifierSpec(ComponentRef("exact-artifact", 1), {}),
-            limits=limits,
-            capabilities=("similarity-search",),
-            conformance_profiles=("core-batch-v1",),
-        )
-        self._exact_verifier = ExactArtifactVerifier()
 
-    def definition(self) -> WorkloadDefinition:
+    # ------------------------------------------------------------------
-        return WorkloadDefinition(
+    # Scientific hooks
-            manifest=self.manifest,
+    # ------------------------------------------------------------------
-            planner=self,
-            runners={MAP_ENTRY_POINT: self},
-            reducers={REDUCE_ENTRY_POINT: self},
-            verifiers={self._exact_verifier.identity.canonical: self._exact_verifier},
-        )
 
     @staticmethod
     def _string(value: object, name: str) -> str:
@@ -283,12 +160,7 @@ class SimilaritySearchSDKWorkload:
             raise ValueError(f"{name} must be a number between 0 and 1")
         return float(value)
 
-    def validate(self, request: JobRequest) -> ValidatedJob:
+    def domain_validate(self, parameters: Mapping[str, Any]) -> None:
-        if request.workload != self.manifest.workload:
-            raise ValueError(
-                "similarity-search received a request for another workload"
-            )
-        parameters = request.parameters
         unknown = set(parameters) - {
             "query_id",
             "query_smiles",
@@ -322,9 +194,8 @@ class SimilaritySearchSDKWorkload:
             "threshold_direction"
         ] not in {"greater", "less"}:
             raise ValueError("threshold_direction must be 'greater' or 'less'")
-        return ValidatedJob(request, self._resolved_parameters(request))
 
-    def _resolved_parameters(self, request: JobRequest) -> dict[str, object]:
+    def resolved_parameters(self, request: JobRequest) -> dict[str, Any]:
         parameters = request.parameters
         query_id = parameters.get("query_id")
         if isinstance(query_id, str):
@@ -334,7 +205,7 @@ class SimilaritySearchSDKWorkload:
                 "kind": "smiles",
                 "value": self._string(parameters.get("query_smiles"), "query_smiles"),
             }
-        resolved: dict[str, object] = {
+        resolved: dict[str, Any] = {
             "query_source": query_source,
             "top_k": self._positive_int(parameters.get("top_k", 20), "top_k"),
             "threshold_direction": parameters.get("threshold_direction", "greater"),
@@ -358,192 +229,54 @@ class SimilaritySearchSDKWorkload:
             )
         return resolved
 
-    def plan(self, job: ValidatedJob, context: PlanningContext) -> WorkflowPlan:
+    def resolved_parameters_for_plan(
-        if not isinstance(job, ValidatedJob):
+        self,
-            raise ValueError("job must be a ValidatedJob")
+        job: ValidatedJob,
-        collection = job.request.inputs.get("input")
+        input_path: Path,
-        if collection is None:
+        resolved: dict[str, Any],
-            raise ValueError("similarity-search requires the input port")
+    ) -> dict[str, Any]:
-        self.input_port.validate_collection(collection, "job input")
+        query_id = job.request.parameters.get("query_id")
-        input_artifact = collection.items[0].artifact
+        if isinstance(query_id, str):
-        input_path = context.catalog.materialize(input_artifact)
+            record = find_molecule_by_id(input_path, query_id)
-        workspace = context.workspace
+            resolved["query_smiles"] = Chem.MolToSmiles(record.molecule, canonical=True)
-        workspace.mkdir(parents=True, exist_ok=True)
+        else:
-        resolved = dict(job.resolved_parameters)
+            supplied = job.request.parameters["query_smiles"]
-        query_smiles = self._resolve_query(input_path, job.request.parameters)
+            assert isinstance(supplied, str)
-        resolved["query_smiles"] = query_smiles
+            molecule = parse_smiles(supplied)
-        max_rows = resolved.get("max_rows")
+            if molecule is None:
-        shard_paths = write_search_shards(
+                raise ValueError("query_smiles is invalid")
+            resolved["query_smiles"] = Chem.MolToSmiles(molecule, canonical=True)
+        return resolved
+
+    def partition_input(
+        self,
+        input_path: Path,
+        parameters: Mapping[str, Any],
+        workspace: Path,
+    ) -> list[Path]:
+        max_rows = parameters.get("max_rows")
+        return write_search_shards(
             input_path,
             workspace,
             self.shard_rows,
             int(max_rows) if isinstance(max_rows, int) else None,
         )
-        task_parameters = {
-            key: value for key, value in resolved.items() if key in set(_MAP_PARAMETERS)
-        }
-        negotiated = context.negotiated
-        map_stage = self.manifest.workflow.stages[0]
-        assert map_stage.verifier is not None
-        tasks: list[TaskSpec] = []
-        for index, path in enumerate(shard_paths):
-            sealed = context.sink.seal(
-                path,
-                declaration=self.input_port.schema,
-            )
-            tasks.append(
-                TaskSpec(
-                    workload=self.manifest.workload,
-                    package_digest=self.manifest.package.digest,
-                    manifest_digest=self.manifest.digest,
-                    trust_mode=job.request.trust_mode,
-                    sdk_api_version=negotiated.sdk_api_version,
-                    protocol_version=negotiated.protocol_version,
-                    manifest_schema_version=self.manifest.manifest_schema_version,
-                    workflow_schema_version=self.manifest.workflow.schema_version,
-                    environment_digest=self.manifest.environment.digest,
-                    verifier=map_stage.verifier,
-                    selected_features=negotiated.selected_features,
-                    optional_fallbacks=negotiated.optional_fallbacks,
-                    task_key=f"map/{index:08d}",
-                    stage_id="map",
-                    parameters=task_parameters,
-                    inputs={"input": ArtifactCollection.single(sealed)},
-                    expected_outputs={"partial": self.partial_port},
-                    resources=map_stage.resources,
-                    execution=map_stage.execution,
-                )
-            )
-        return WorkflowPlan(
-            workload=self.manifest.workload,
-            package_digest=self.manifest.package.digest,
-            manifest_digest=self.manifest.digest,
-            trust_mode=job.request.trust_mode,
-            sdk_api_version=negotiated.sdk_api_version,
-            protocol_version=negotiated.protocol_version,
-            manifest_schema_version=self.manifest.manifest_schema_version,
-            workflow_schema_version=self.manifest.workflow.schema_version,
-            environment_digest=self.manifest.environment.digest,
-            verifier=self.manifest.verifier.verifier,
-            selected_features=negotiated.selected_features,
-            optional_fallbacks=negotiated.optional_fallbacks,
-            workflow_id=self.manifest.workflow.workflow_id,
-            resolved_parameters=resolved,
-            tasks=tuple(tasks),
-        )
 
-    @staticmethod
+    def compute_shard(
-    def _resolve_query(input_path: Path, parameters: Mapping[str, object]) -> str:
+        self,
-        query_id = parameters.get("query_id")
+        inputs: Mapping[str, Path],
-        if isinstance(query_id, str):
+        parameters: Mapping[str, Any],
-            record = find_molecule_by_id(input_path, query_id)
+        output_path: Path,
-            return Chem.MolToSmiles(record.molecule, canonical=True)
+    ) -> Mapping[str, int | float]:
-        supplied = parameters["query_smiles"]
+        return run_search_shard(inputs["input"], parameters, output_path)
-        assert isinstance(supplied, str)
-        molecule = parse_smiles(supplied)
-        if molecule is None:
-            raise ValueError("query_smiles is invalid")
-        return Chem.MolToSmiles(molecule, canonical=True)
 
-    def run(self, context: TaskContext) -> OutputManifest:
+    def reduce_partials(
-        context.cancellation.raise_if_cancelled()
+        self,
-        collection = context.task.inputs.get("input")
+        partial_paths: Sequence[Path],
-        if collection is None:
+        parameters: Mapping[str, Any],
-            raise ValueError("search map task requires one input collection")
+        output_path: Path,
-        self.input_port.validate_collection(collection, "search map input")
+    ) -> Mapping[str, int | float]:
-        source = context.catalog.materialize(collection.items[0].artifact)
+        return merge_search_partials(partial_paths, parameters, output_path)
-        workspace = context.workspace
-        workspace.mkdir(parents=True, exist_ok=True)
-        input_path = workspace / "input"
-        output_path = workspace / "result.csv"
-        if source.resolve() != input_path.resolve():
-            shutil.copyfile(source, input_path)
-        metrics = run_search_shard(
-            input_path,
-            context.task.parameters,
-            output_path,
-        )
-        context.cancellation.raise_if_cancelled()
-        sealed = context.sink.seal(
-            output_path,
-            declaration=self.partial_port.schema,
-        )
-        return OutputManifest(
-            context.task.task_key,
-            {"partial": ArtifactCollection.single(sealed)},
-            metrics,
-            context.provenance,
-        ).validate_against(
-            context.task.expected_outputs,
-            max_output_bytes=self.manifest.limits.max_output_bytes,
-        )
-
-    def reduce(self, context: ReduceContext) -> OutputManifest:
-        context.cancellation.raise_if_cancelled()
-        collection = context.accepted_inputs.get("partials")
-        if (
-            collection is None
-            or collection.kind is not CollectionKind.KEYED
-            or not collection.items
-        ):
-            raise ValueError(
-                "search reducer requires a non-empty keyed partial collection"
-            )
-        self.manifest.workflow.stages[1].inputs["partials"].validate_collection(
-            collection,
-            "search reducer partials",
-        )
-        workspace = context.workspace
-        workspace.mkdir(parents=True, exist_ok=True)
-        indexed_items: list[tuple[int, ArtifactItem]] = []
-        for item in collection.items:
-            key = item.key or ""
-            prefix = "map."
-            raw_index = key[len(prefix) :] if key.startswith(prefix) else ""
-            if len(raw_index) != 8 or not raw_index.isdigit():
-                raise ValueError("search partial key must use map.<eight-digit-index>")
-            indexed_items.append((int(raw_index), item))
-        expected_keys = context.task.expected_input_keys.get("partials")
-        if expected_keys is None or {item.key for item in collection.items} != set(
-            expected_keys
-        ):
-            raise ValueError(
-                "search partial keys do not match the coordinator expected set"
-            )
-        if sorted(index for index, _ in indexed_items) != list(
-            range(len(indexed_items))
-        ):
-            raise ValueError("search partial keys must be complete and contiguous")
-        partial_paths: list[Path] = []
-        for index, item in sorted(indexed_items):
-            artifact: ArtifactRef = item.artifact
-            source = context.catalog.materialize(artifact)
-            target = workspace / artifact.artifact_id
-            if source.resolve() != target.resolve():
-                shutil.copyfile(source, target)
-            if _sha256_file(target) != artifact.sha256:
-                raise ValueError("materialized partial checksum does not match")
-            partial_paths.append(target)
-        result_path = workspace / "result.csv"
-        metrics = merge_search_partials(
-            partial_paths,
-            context.task.parameters,
-            result_path,
-        )
-        context.cancellation.raise_if_cancelled()
-        sealed = context.sink.seal(
-            result_path,
-            declaration=self.output_port.schema,
-        )
-        return OutputManifest(
-            context.task.task_key,
-            {"result": ArtifactCollection.single(sealed)},
-            metrics,
-            context.provenance,
-        ).validate_against(
-            context.task.expected_outputs,
-            max_output_bytes=self.manifest.limits.max_output_bytes,
-        )
 
 
 def similarity_search_sdk_definition(

scimesh/workloads/workload_cli.py

@@ -0,0 +1,167 @@
+"""Generic SDK workload runner CLI: ``scimesh workload list|run``.
+
+This is a generic SDK tool, not a workload. It lists the enabled SDK-built
+workloads and executes any of them locally through ``LocalCoreBatchExecutor``,
+so a user-written workload package can be inspected and verified without
+touching any other part of the program.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import shutil
+import tempfile
+from pathlib import Path
+
+from scimesh.sdk import (
+    ArtifactCollection,
+    JobRequest,
+    LocalArtifactStore,
+    LocalCoreBatchExecutor,
+)
+from scimesh.sdk.registry import workload_allowlist_from_json
+from scimesh.workloads.library import default_sdk_registry, default_sdk_runtime
+
+
+class WorkloadCLI:
+    """Inspect and run SDK-built workloads from the command line."""
+
+    name = "workload"
+    help = "List and run SDK-built workloads locally."
+
+    def configure_parser(self, parser: argparse.ArgumentParser) -> None:
+        subparsers = parser.add_subparsers(dest="workload_command", required=True)
+
+        list_parser = subparsers.add_parser(
+            "list", help="List installed and enabled SDK workloads."
+        )
+        list_parser.set_defaults(workload_handler=self.list_workloads)
+
+        run_parser = subparsers.add_parser(
+            "run", help="Run one SDK workload locally against an input file."
+        )
+        run_parser.add_argument(
+            "name", help="Workload name, for example descriptor-batch"
+        )
+        run_parser.add_argument(
+            "--version", help="Exact workload version (default: the enabled one)"
+        )
+        run_parser.add_argument(
+            "--input", required=True, type=Path, help="Input dataset file"
+        )
+        run_parser.add_argument(
+            "--params", default="{}", help="Job parameters as a JSON object"
+        )
+        run_parser.add_argument(
+            "--shard-rows",
+            type=int,
+            default=10_000,
+            help="Rows per planned shard for workloads that shard by rows",
+        )
+        run_parser.add_argument(
+            "-o",
+            "--output",
+            type=Path,
+            default=Path("workload_result.csv"),
+            help="Output path for the final artifact",
+        )
+        run_parser.add_argument(
+            "--work-dir",
+            type=Path,
+            help="Temporary working directory (default: a fresh temporary directory)",
+        )
+        run_parser.set_defaults(workload_handler=self.run_workload)
+
+    def run(self, args: argparse.Namespace) -> int:
+        handler = getattr(args, "workload_handler", None)
+        if handler is None:
+            raise ValueError("select a workload subcommand: list or run")
+        return handler(args)
+
+    @staticmethod
+    def _registry(args: argparse.Namespace):
+        import os
+
+        allowlist = workload_allowlist_from_json(
+            os.getenv("SCIMESH_WORKLOAD_ALLOWLIST")
+        )
+        return default_sdk_registry(
+            shard_rows=getattr(args, "shard_rows", 10_000),
+            allowlist=allowlist,
+        )
+
+    def list_workloads(self, args: argparse.Namespace) -> int:
+        registry = self._registry(args)
+        descriptions = registry.descriptions()
+        if not descriptions:
+            print("No SDK workloads are installed or enabled.")
+            return 0
+        width = max(len(item.workload.name) for item in descriptions)
+        for item in sorted(descriptions, key=lambda value: value.workload.name):
+            digest = item.package_digest.removeprefix("sha256:")[:12]
+            state = "enabled" if item.enabled else "disabled"
+            print(
+                f"{item.workload.name:<{width}}  {item.workload.version}  "
+                f"{item.description}  [{state} {digest}]"
+            )
+        return 0
+
+    def run_workload(self, args: argparse.Namespace) -> int:
+        registry = self._registry(args)
+        descriptions = registry.descriptions()
+        try:
+            parameters = json.loads(args.params)
+        except (TypeError, json.JSONDecodeError, RecursionError) as error:
+            raise ValueError("--params must be a valid JSON object") from error
+        if not isinstance(parameters, dict):
+            raise ValueError("--params must be a JSON object")
+        description = next(
+            (
+                item
+                for item in descriptions
+                if item.workload.name == args.name
+                and (args.version is None or item.workload.version == args.version)
+            ),
+            None,
+        )
+        if description is None:
+            raise ValueError(f"unknown or disabled SDK workload: {args.name}")
+        definition, _ = registry.require(
+            description.workload.name,
+            description.workload.version,
+            description.package_digest,
+        )
+        runtime = default_sdk_runtime(
+            workload_capabilities=tuple(item.workload.name for item in descriptions),
+            environment_digests=(definition.manifest.environment.digest,),
+        )
+        if not args.input.is_file():
+            raise ValueError(f"input file does not exist: {args.input}")
+        with tempfile.TemporaryDirectory(prefix="scimesh-workload-") as temporary:
+            root = Path(temporary)
+            store = LocalArtifactStore(root / "artifacts")
+            artifact = store.import_file(
+                args.input,
+                declaration=definition.manifest.inputs["input"].schema,
+            )
+            request = JobRequest(
+                workload=definition.manifest.workload,
+                parameters=parameters,
+                inputs={"input": ArtifactCollection.single(artifact)},
+            )
+            result = LocalCoreBatchExecutor(
+                registry,
+                runtime,
+                store,
+                args.work_dir or root / "attempts",
+            ).execute(request, description.package_digest)
+            result_artifact = result.outputs["result"].items[0].artifact
+            source = store.materialize(result_artifact)
+            args.output.parent.mkdir(parents=True, exist_ok=True)
+            shutil.copyfile(source, args.output)
+        print(
+            f"Saved {description.workload.name} result to {args.output} "
+            f"(metrics: {dict(result.metrics)})"
+        )
+        return 0

tests/test_cli_workload.py

@@ -0,0 +1,229 @@
+"""Tests for the generic ``scimesh workload`` CLI."""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+from scimesh.cli import main
+
+
+def test_workload_cli_lists_sdk_workloads(capsys: object) -> None:
+    assert main(["workload", "list"]) == 0
+    output = capsys.readouterr().out
+    assert "descriptor-batch" in output
+    assert "similarity-graph" in output
+    assert "similarity-search" in output
+    assert "enabled" in output
+
+
+def test_workload_cli_runs_descriptor_batch(tmp_path: Path, capsys: object) -> None:
+    dataset = tmp_path / "molecules.tsv"
+    dataset.write_text(
+        "chembl_id\tcanonical_smiles\nA\tCCO\nB\tCCCC\nC\tCCN\n",
+        encoding="utf-8",
+    )
+    output = tmp_path / "descriptors.csv"
+
+    code = main(
+        [
+            "workload",
+            "run",
+            "descriptor-batch",
+            "--input",
+            str(dataset),
+            "--params",
+            '{"skip_invalid": true}',
+            "--shard-rows",
+            "2",
+            "-o",
+            str(output),
+        ]
+    )
+
+    assert code == 0
+    lines = output.read_text(encoding="utf-8").splitlines()
+    assert lines[0].startswith("chembl_id,canonical_smiles,ExactMolWt")
+    assert len(lines) == 4
+    assert "rows_emitted" in capsys.readouterr().out
+
+
+def test_workload_cli_runs_similarity_search(tmp_path: Path) -> None:
+    dataset = tmp_path / "molecules.tsv"
+    dataset.write_text(
+        "chembl_id\tcanonical_smiles\nQUERY\tCCO\nMATCH\tCCCO\n",
+        encoding="utf-8",
+    )
+    output = tmp_path / "search.csv"
+
+    code = main(
+        [
+            "workload",
+            "run",
+            "similarity-search",
+            "--input",
+            str(dataset),
+            "--params",
+            '{"query_smiles": "CCO", "top_k": 5, "progress_every": 0}',
+            "--shard-rows",
+            "2",
+            "-o",
+            str(output),
+        ]
+    )
+
+    assert code == 0
+    lines = output.read_text(encoding="utf-8").splitlines()
+    assert lines[0] == "rank,chembl_id,canonical_smiles,similarity"
+    assert len(lines) == 2
+
+
+def test_workload_cli_rejects_unknown_or_missing_workload(tmp_path: Path) -> None:
+    import pytest
+
+    dataset = tmp_path / "molecules.tsv"
+    dataset.write_text("chembl_id\tcanonical_smiles\nA\tCCO\n", encoding="utf-8")
+    assert main(["workload", "run", "no-such-workload", "--input", str(dataset)]) == 1
+    with pytest.raises(SystemExit):
+        main(["workload", "run", "descriptor-batch"])
+
+
+def test_workload_cli_rejects_invalid_params_json(tmp_path: Path) -> None:
+    dataset = tmp_path / "molecules.tsv"
+    dataset.write_text("chembl_id\tcanonical_smiles\nA\tCCO\n", encoding="utf-8")
+    assert (
+        main(
+            [
+                "workload",
+                "run",
+                "descriptor-batch",
+                "--input",
+                str(dataset),
+                "--params",
+                "{broken",
+            ]
+        )
+        == 1
+    )
+
+
+def test_workload_cli_runs_an_allowlisted_custom_workload(
+    tmp_path: Path, monkeypatch: object, capsys: object
+) -> None:
+    import csv
+
+    from scimesh.sdk import (
+        ArtifactSchema,
+        ComponentRef,
+        MapReduceWorkload,
+        PortSpec,
+        SchemaRef,
+        WorkloadId,
+    )
+    from scimesh.sdk.registry import WorkloadRegistry
+    from scimesh.workloads.environment import (
+        current_environment_digest,
+        current_scimesh_package_digest,
+    )
+
+    class CountRowsWorkload(MapReduceWorkload):
+        workload_id = WorkloadId("count-rows", "1.0.0")
+        description = "Count TSV data rows per shard."
+        parameters_schema = {
+            "type": "object",
+            "additionalProperties": False,
+            "properties": {},
+        }
+        input_port = PortSpec(
+            ArtifactSchema(
+                SchemaRef("molecule-table", 1),
+                "text/tab-separated-values",
+                "utf-8",
+                10**9,
+                ComponentRef("delimited-table", 1),
+                validator_configuration={
+                    "required_columns": ["canonical_smiles", "chembl_id"]
+                },
+                max_records=10**8,
+            )
+        )
+        partial_port = output_port = PortSpec(
+            ArtifactSchema(
+                SchemaRef("count-table", 1),
+                "text/csv",
+                "utf-8",
+                10**9,
+                ComponentRef("delimited-table", 1),
+                validator_configuration={"columns": ["id", "rows"]},
+                max_records=10**8,
+            )
+        )
+
+        def partition_input(self, input_path, parameters, workspace):
+            paths = []
+            with input_path.open(encoding="utf-8", newline="") as source:
+                for index, row in enumerate(csv.DictReader(source, delimiter="\t")):
+                    path = workspace / f"shard-{index}.tsv"
+                    path.write_text(
+                        "chembl_id\tcanonical_smiles\n"
+                        + row["chembl_id"]
+                        + "\t"
+                        + row["canonical_smiles"]
+                        + "\n",
+                        encoding="utf-8",
+                    )
+                    paths.append(path)
+            return paths
+
+        def compute_shard(self, inputs, parameters, output_path):
+            lines = inputs["input"].read_text(encoding="utf-8").splitlines()
+            rows = max(len(lines) - 1, 0)
+            output_path.write_text(
+                "id,rows\nshard," + str(rows) + "\n", encoding="utf-8"
+            )
+            return {"rows": rows}
+
+        def reduce_partials(self, partial_paths, parameters, output_path):
+            with output_path.open("w", encoding="utf-8") as destination:
+                destination.write("id,rows\n")
+                total = 0
+                for partial in partial_paths:
+                    rows = partial.read_text(encoding="utf-8").splitlines()[1:]
+                    destination.write("".join(row + "\n" for row in rows))
+                    total += len(rows)
+            return {"rows_total": total, "partial_count": len(partial_paths)}
+
+    definition = CountRowsWorkload(
+        package_digest=current_scimesh_package_digest(),
+        environment_digest=current_environment_digest(),
+    ).definition()
+
+    def fake_discover(self: WorkloadRegistry, allowlist) -> None:
+        self.register(definition, enabled=True)
+
+    monkeypatch.setattr(WorkloadRegistry, "discover_installed", fake_discover)
+    monkeypatch.setenv(
+        "SCIMESH_WORKLOAD_ALLOWLIST",
+        '[{"distribution": "scimesh", "name": "count-rows", "version": "1.0.0", '
+        '"digest": "' + current_scimesh_package_digest() + '"}]',
+    )
+
+    dataset = tmp_path / "molecules.tsv"
+    dataset.write_text(
+        "chembl_id\tcanonical_smiles\nA\tCCO\nB\tCCCC\n", encoding="utf-8"
+    )
+    output = tmp_path / "counts.csv"
+    assert (
+        main(
+            [
+                "workload",
+                "run",
+                "count-rows",
+                "--input",
+                str(dataset),
+                "-o",
+                str(output),
+            ]
+        )
+        == 0
+    )
+    assert output.read_text(encoding="utf-8") == "id,rows\nshard,1\nshard,1\n"

tests/test_sdk_batch.py

@@ -0,0 +1,305 @@
+"""Tests for the MapReduceWorkload authoring scaffold."""
+
+from __future__ import annotations
+
+import csv
+from dataclasses import replace
+from pathlib import Path
+
+import pytest
+
+from scimesh.sdk import (
+    ArtifactCollection,
+    ArtifactSchema,
+    ComponentRef,
+    DeterminismProfile,
+    JobRequest,
+    LocalArtifactStore,
+    LocalCoreBatchExecutor,
+    LocalPlanningContext,
+    MapReduceWorkload,
+    PortSpec,
+    SchemaRef,
+    StageKind,
+    TrustMode,
+    WorkloadId,
+    WorkloadRegistry,
+    assert_manifest_round_trip,
+)
+from scimesh.workloads.library import default_sdk_runtime
+from scimesh.workloads.environment import (
+    current_environment_digest,
+    current_scimesh_package_digest,
+)
+
+
+def _molecule_port() -> PortSpec:
+    return PortSpec(
+        ArtifactSchema(
+            SchemaRef("molecule-table", 1),
+            "text/tab-separated-values",
+            "utf-8",
+            10**9,
+            ComponentRef("delimited-table", 1),
+            validator_configuration={
+                "required_columns": ["canonical_smiles", "chembl_id"]
+            },
+            max_records=10**8,
+        )
+    )
+
+
+def _count_port() -> PortSpec:
+    return PortSpec(
+        ArtifactSchema(
+            SchemaRef("count-table", 1),
+            "text/csv",
+            "utf-8",
+            10**9,
+            ComponentRef("delimited-table", 1),
+            validator_configuration={"columns": ["id", "rows"]},
+            max_records=10**8,
+        )
+    )
+
+
+class CountRowsWorkload(MapReduceWorkload):
+    """A minimal author-written workload: three scientific hooks only."""
+
+    workload_id = WorkloadId("count-rows", "1.0.0")
+    description = "Count TSV data rows per shard and concatenate the counts."
+    parameters_schema = {
+        "type": "object",
+        "additionalProperties": False,
+        "properties": {"prefix": {"type": "string", "minLength": 1, "maxLength": 50}},
+    }
+    input_port = _molecule_port()
+    partial_port = _count_port()
+    output_port = _count_port()
+    map_parameter_names = ("prefix",)
+    reduce_parameter_names = ("prefix",)
+
+    def partition_input(self, input_path, parameters, workspace):
+        paths = []
+        with input_path.open(encoding="utf-8", newline="") as source:
+            for index, row in enumerate(csv.DictReader(source, delimiter="\t")):
+                path = workspace / f"shard-{index}.tsv"
+                path.write_text(
+                    "chembl_id\tcanonical_smiles\n"
+                    + row["chembl_id"]
+                    + "\t"
+                    + row["canonical_smiles"]
+                    + "\n",
+                    encoding="utf-8",
+                )
+                paths.append(path)
+        return paths
+
+    def compute_shard(self, inputs, parameters, output_path):
+        lines = inputs["input"].read_text(encoding="utf-8").splitlines()
+        rows = max(len(lines) - 1, 0)
+        output_path.write_text(
+            "id,rows\n" + parameters.get("prefix", "shard") + "," + str(rows) + "\n",
+            encoding="utf-8",
+        )
+        return {"rows": rows}  # type: ignore[return-value]
+
+    def reduce_partials(self, partial_paths, parameters, output_path):
+        total = 0
+        with output_path.open("w", encoding="utf-8") as destination:
+            destination.write("id,rows\n")
+            for partial in partial_paths:
+                for index, line in enumerate(
+                    partial.read_text(encoding="utf-8").splitlines()
+                ):
+                    if index == 0:
+                        continue
+                    destination.write(line + "\n")
+                    total += int(line.split(",")[1])
+        return {"rows_total": total, "partial_count": len(partial_paths)}  # type: ignore[return-value]
+
+
+def _registered_count_rows():
+    workload = CountRowsWorkload(
+        package_digest=current_scimesh_package_digest(),
+        environment_digest=current_environment_digest(),
+    )
+    registry = WorkloadRegistry()
+    registry.register(workload.definition(), enabled=True)
+    runtime = replace(
+        default_sdk_runtime(),
+        workload_capabilities=(
+            *default_sdk_runtime().workload_capabilities,
+            "count-rows",
+        ),
+    )
+    return workload, registry, runtime
+
+
+def _write_dataset(path: Path) -> None:
+    path.write_text(
+        "chembl_id\tcanonical_smiles\nA\tCCO\nB\tCCCC\nC\tCCN\n",
+        encoding="utf-8",
+    )
+
+
+def _request(workload, store, dataset) -> JobRequest:
+    artifact = store.import_file(
+        dataset,
+        declaration=workload.manifest.inputs["input"].schema,
+    )
+    return JobRequest(
+        workload=workload.manifest.workload,
+        parameters={"prefix": "x"},
+        inputs={"input": ArtifactCollection.single(artifact)},
+    )
+
+
+def test_map_reduce_scaffold_assembles_the_manifest_and_runs(tmp_path: Path) -> None:
+    workload, registry, runtime = _registered_count_rows()
+    manifest = workload.manifest
+
+    assert manifest.workload.name == "count-rows"
+    assert manifest.workload.version == "1.0.0"
+    assert manifest.determinism is DeterminismProfile.BYTE_EXACT
+    assert manifest.verifier.verifier.canonical == "exact-artifact@1"
+    assert set(mode.value for mode in manifest.trust_modes) == {
+        "trusted",
+        "untrusted_quorum",
+    }
+    assert [stage.kind for stage in manifest.workflow.stages] == [
+        StageKind.MAP,
+        StageKind.REDUCE,
+    ]
+    assert set(workload.definition().runners) == {
+        manifest.workflow.stages[0].entry_point
+    }
+    assert set(workload.definition().reducers) == {
+        manifest.workflow.stages[1].entry_point
+    }
+    assert_manifest_round_trip(manifest)
+
+    dataset = tmp_path / "molecules.tsv"
+    _write_dataset(dataset)
+    store = LocalArtifactStore(tmp_path / "artifacts")
+    result = LocalCoreBatchExecutor(
+        registry,
+        runtime,
+        store,
+        tmp_path / "work",
+    ).execute(_request(workload, store, dataset), workload.manifest.package.digest)
+
+    assert result.task_key == "reduce/final"
+    assert dict(result.metrics) == {"rows_total": 3, "partial_count": 3}
+    text = store.materialize(result.outputs["result"].items[0].artifact).read_text(
+        encoding="utf-8"
+    )
+    assert text == "id,rows\nx,1\nx,1\nx,1\n"
+
+
+def test_map_reduce_scaffold_derives_pinned_plans_and_parameters(
+    tmp_path: Path,
+) -> None:
+    workload, registry, runtime = _registered_count_rows()
+    dataset = tmp_path / "molecules.tsv"
+    _write_dataset(dataset)
+    store = LocalArtifactStore(tmp_path / "artifacts")
+    request = _request(workload, store, dataset)
+    input_artifact = request.inputs["input"].items[0].artifact
+
+    plan = registry.plan(
+        request,
+        workload.manifest.package.digest,
+        runtime,
+        LocalPlanningContext(
+            store,
+            store,
+            tmp_path / "plan",
+            allowed_artifacts=(input_artifact,),
+        ),
+    )
+    assert [task.task_key for task in plan.tasks] == [
+        "map/00000000",
+        "map/00000001",
+        "map/00000002",
+    ]
+    assert all(task.parameters == {"prefix": "x"} for task in plan.tasks)
+    assert all(task.package_digest == plan.package_digest for task in plan.tasks)
+    assert all(task.manifest_digest == plan.manifest_digest for task in plan.tasks)
+    assert all(task.trust_mode is TrustMode.TRUSTED for task in plan.tasks)
+
+
+def test_map_reduce_scaffold_requires_scientific_hooks() -> None:
+    class MissingHooksWorkload(MapReduceWorkload):
+        workload_id = WorkloadId("missing-hooks", "1.0.0")
+        description = "A workload that forgets its scientific hooks."
+        parameters_schema = {
+            "type": "object",
+            "additionalProperties": False,
+            "properties": {},
+        }
+        input_port = _molecule_port()
+        partial_port = _count_port()
+        output_port = _count_port()
+
+    workload = MissingHooksWorkload(
+        package_digest=current_scimesh_package_digest(),
+        environment_digest=current_environment_digest(),
+    )
+    with pytest.raises(NotImplementedError, match="partition_input"):
+        workload.partition_input(Path("input"), {}, Path("workspace"))
+    with pytest.raises(NotImplementedError, match="compute_shard"):
+        workload.compute_shard({}, {}, Path("output"))
+    with pytest.raises(NotImplementedError, match="reduce_partials"):
+        workload.reduce_partials([], {}, Path("output"))
+
+
+def test_map_reduce_scaffold_default_partial_keys_are_contiguous() -> None:
+    workload = CountRowsWorkload(
+        package_digest=current_scimesh_package_digest(),
+        environment_digest=current_environment_digest(),
+    )
+    assert workload.parse_partial_key("map.00000000") == 0
+    assert workload.parse_partial_key("map.00000002") == 2
+    with pytest.raises(ValueError, match="eight-digit-index"):
+        workload.parse_partial_key("map.0")
+    workload.validate_partial_keys((0, 1, 2))
+    with pytest.raises(ValueError, match="complete and contiguous"):
+        workload.validate_partial_keys((0, 2))
+    with pytest.raises(ValueError, match="complete and contiguous"):
+        workload.validate_partial_keys((0, 0, 1))
+
+
+def test_map_reduce_scaffold_rejects_domain_invalid_parameters(tmp_path: Path) -> None:
+    workload, registry, runtime = _registered_count_rows()
+    dataset = tmp_path / "molecules.tsv"
+    _write_dataset(dataset)
+    store = LocalArtifactStore(tmp_path / "artifacts")
+    artifact = store.import_file(
+        dataset,
+        declaration=workload.manifest.inputs["input"].schema,
+    )
+
+    class StrictCountRows(CountRowsWorkload):
+        def domain_validate(self, parameters):
+            if "prefix" not in parameters:
+                raise ValueError("prefix is required")
+
+    strict = StrictCountRows(
+        package_digest=current_scimesh_package_digest(),
+        environment_digest=current_environment_digest(),
+    )
+    registry2 = WorkloadRegistry()
+    registry2.register(strict.definition(), enabled=True)
+    request = JobRequest(
+        workload=strict.manifest.workload,
+        parameters={},
+        inputs={"input": ArtifactCollection.single(artifact)},
+    )
+    with pytest.raises(ValueError, match="prefix is required"):
+        registry2.plan(
+            request,
+            strict.manifest.package.digest,
+            runtime,
+            LocalPlanningContext(store, store, tmp_path / "plan"),
+        )

tests/test_worker_daemon.py

@@ -10,7 +10,7 @@ from urllib.request import Request
 
 import pytest
 
-from scimesh.worker.config import WorkerConfig
+from scimesh.worker.config import WorkerConfig, _workload_allowlist
 from scimesh.worker import cli as worker_cli
 from scimesh.worker.cli import build_parser
 from scimesh.worker.coordinator import CoordinatorTransientError
@@ -579,7 +579,7 @@ def test_runner_executes_search_through_the_sdk_and_rejects_graph(
     )
 
 
-def test_runner_resolves_query_id_from_the_shard_and_rejects_plan_time_options(
+def test_runner_resolves_query_id_from_the_shard_and_rejects_plan_time_parameters(
     tmp_path: Path,
 ) -> None:
     task_dir = tmp_path / "search"
@@ -607,7 +607,7 @@ def test_runner_resolves_query_id_from_the_shard_and_rejects_plan_time_options(
         InputArtifact("https://example/input", "a" * 64),
         {"query_smiles": "CCO", "max_rows": 1},
     )
-    with pytest.raises(ValueError, match="unsupported runner parameters"):
+    with pytest.raises(ValueError, match="outside the stage projection"):
         SciMeshRunner().run(with_max_rows, task_dir)
 
 
@@ -732,3 +732,111 @@ def test_worker_registration_sets_returned_identity(tmp_path: Path) -> None:
     worker._register_worker()
     assert worker.worker_id == "11111111-1111-4111-8111-111111111111"
     assert worker.config.heartbeat_interval == 15
+
+
+def test_runner_executes_an_arbitrary_sdk_workload(tmp_path: Path) -> None:
+    from scimesh.workloads.descriptors import descriptor_batch_sdk_definition
+
+    content = b"chembl_id\tcanonical_smiles\nA\tCCO\nB\tCCCC\n"
+    task = ClaimedTask(
+        "task-1",
+        1,
+        (datetime.now(timezone.utc) + timedelta(seconds=60)).isoformat(),
+        "descriptor-batch",
+        InputArtifact("https://example.test/input", hashlib.sha256(content).hexdigest()),
+        {"skip_invalid": True},
+    )
+    task_dir = tmp_path / "task-1" / "1"
+    task_dir.mkdir(parents=True)
+    (task_dir / "input").write_bytes(content)
+    runner = SciMeshRunner(
+        definitions={
+            "descriptor-batch": descriptor_batch_sdk_definition().definition()
+        }
+    )
+
+    result = runner.run(task, task_dir)
+    header = result.artifacts[0].path.read_text(encoding="utf-8").splitlines()[0]
+    assert header.startswith("chembl_id,canonical_smiles,ExactMolWt")
+    assert result.metrics["rows_emitted"] == 2
+
+
+def test_runner_rejects_workloads_outside_the_v1_single_input_contract(
+    tmp_path: Path,
+) -> None:
+    from scimesh.workloads.graph import similarity_graph_sdk_definition
+
+    content = b"chembl_id\tcanonical_smiles\nA\tCCO\nB\tCCCC\n"
+    task = ClaimedTask(
+        "graph-task",
+        1,
+        (datetime.now(timezone.utc) + timedelta(seconds=60)).isoformat(),
+        "similarity-graph",
+        InputArtifact("https://example.test/input", hashlib.sha256(content).hexdigest()),
+        {"threshold": 0.5},
+    )
+    task_dir = tmp_path / "graph"
+    task_dir.mkdir(parents=True)
+    (task_dir / "input").write_bytes(content)
+    runner = SciMeshRunner(
+        definitions={
+            "similarity-graph": similarity_graph_sdk_definition().definition()
+        }
+    )
+
+    with pytest.raises(ValueError, match="v1 single-input contract"):
+        runner.run(task, task_dir)
+
+
+def test_runner_for_worker_discovers_allowlisted_installed_workloads(
+    monkeypatch: pytest.MonkeyPatch, tmp_path: Path
+) -> None:
+    from scimesh.sdk.registry import WorkloadRegistry
+    from scimesh.workloads.search import similarity_search_sdk_definition
+
+    definition = similarity_search_sdk_definition().definition()
+
+    def fake_discover(self: WorkloadRegistry, allowlist) -> None:
+        assert len(allowlist) == 1
+        self.register(definition, enabled=True)
+
+    monkeypatch.setattr(WorkloadRegistry, "discover_installed", fake_discover)
+    allowlist = _workload_allowlist(
+        '[{"distribution": "scimesh", "name": "similarity-search", '
+        '"version": "1.0.0", "digest": "sha256:' + "a" * 64 + '"}]'
+    )
+    config = WorkerConfig(
+        "https://example.test", "worker-1", tmp_path / "work",
+        capabilities=("similarity-search",),
+        workload_allowlist=allowlist,
+    )
+    runner = SciMeshRunner.for_worker(config)
+    assert set(runner._definitions) == {"similarity-search"}
+
+
+def test_worker_config_parses_capabilities_and_workload_allowlist(
+    monkeypatch: pytest.MonkeyPatch, tmp_path: Path
+) -> None:
+    monkeypatch.setenv("SCIMESH_CAPABILITIES", "similarity-search,descriptor-batch")
+    config = WorkerConfig.from_environment(
+        {"coordinator_url": "https://example.test", "work_dir": tmp_path}
+    )
+    assert config.capabilities == ("similarity-search", "descriptor-batch")
+    assert config.workload_allowlist == ()
+
+    monkeypatch.setenv(
+        "SCIMESH_WORKLOAD_ALLOWLIST",
+        '[{"distribution": "scimesh", "name": "descriptor-batch", '
+        '"version": "1.0.0", "digest": "sha256:' + "b" * 64 + '"}]',
+    )
+    config = WorkerConfig.from_environment(
+        {"coordinator_url": "https://example.test", "work_dir": tmp_path}
+    )
+    assert len(config.workload_allowlist) == 1
+    assert config.workload_allowlist[0].workload.name == "descriptor-batch"
+
+    monkeypatch.setenv("SCIMESH_WORKLOAD_ALLOWLIST", "not-json")
+    with pytest.raises(ValueError, match="valid JSON"):
+        WorkerConfig.from_environment(
+            {"coordinator_url": "https://example.test", "work_dir": tmp_path}
+        )