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workflows/

The versioned science-workflow benchmark's manifests: thirteen workflows and 46 cases, each workflow JSON declaring what a run is supposed to do and what counts as having done it. The root-level next-round-acceptance.json is a separate Stage 0 field/safety pack, not a fourteenth science workflow.

They live in the repository rather than in a fixture directory for one reason: a case change has to be a reviewable diff. The runner that executes them is openai4s/benchmark/, and every step it takes drives production code — the real Store, the real kernel manager, the real host dispatcher, the real compute manager. What gets injected is only what cannot run offline: the model, the network, and a package manager.

A declared outcome is part of the contract, not a status column. failure, permission_denied, recovered and provenance cases fail when the run succeeds, because a benchmark that scores "no exception" measures nothing about the half of the system whose job is to refuse.

Workflow What it covers
next-round-acceptance.json Strict Stage 0 pack for six field paths, seven safety actions, and denominator-explicit baseline metrics
artifact-lineage/ A derived artifact carries its lineage
codebase-mode/ A source deliverable, and whether the Host believes the claim about it
delegation/ What the parent is told a child did
environment-provenance/ An artifact's environment provenance
environment-transaction/ plan -> apply -> rollback as a transaction
evidence-package/ Exporting and verifying an evidence package
permission-boundary/ The workspace boundary refuses a write outside it
python-analysis/ Python analysis producing a traceable artifact
r-analysis/ R is its own channel, not a wrapper
remote-compute/ submit -> poll -> harvest against a real shell
science-retrieval/ Scientific retrieval with source evidence
telemetry-identity/ Revoking telemetry destroys the identity with it
tool-bringup/ Tool bring-up: build, weights, canary, admission, frozen record

Replay the strict Stage 0 pack, with a JSON report suitable for a gate, using openai4s benchmark --acceptance --json. A matching baseline gap is printed as BASELINE, never as a current capability. The loader freezes the manifest's path IDs, claims, execution modes, assertion keys, expected values, and canonical content digest under one pack_version; a semantic edit without a reviewed version/digest is rejected rather than silently changing the baseline. The current 2026-08-16.2 manifest requires the Reviewer observation to prove that the formal workspace fingerprint remained unchanged.