Factory Enforcement

World-class docs are not enough by themselves. posttrainllm needs validators that refuse weak artifacts.

Enforcement Layers

Layer	Tool	What It Checks
Run bundle schema	`posttrainllm factory-run validate runs/<id>`	Core typed JSON bundle: config, dataset, baseline, candidate, decision, optional artifact
Publish evidence	`posttrainllm factory-run publish-check runs/<id>`	Required evidence files, report sections, slice metrics, trace review, decision, ship/package constraints
Portable publish smoke	`python3 scripts/check_factory_run_publish.py runs/<id>`	Same policy in a no-build Python checker for CI/smokes
Target-specific smokes	`evals/*-smoke.sh`	No-GPU fixture checks for scripts and report helpers
Public artifact review	`docs/factory/public-artifacts.md`	Human-readable release state, blockers, competition context

Publish Check

Report-only artifacts may have blockers, but they still need evidence:

posttrainllm factory-run publish-check --allow-report-only runs/<id>

Shipped artifacts are stricter:

posttrainllm factory-run publish-check runs/<id>

For decision=ship, the check requires:

artifact.json
artifact.shipped=true
artifact.package_dir
no blockers in decision.blocked_by

For every run, the check requires:

baseline and candidate JSON
dataset manifest
train log
report
slice-metrics.json
trace_review.md
provenance.json
report sections for decision, target, data, eval, performance, failures, and next action

Current Gap

The native strict check exists, and the Python checker remains as a portable smoke. A later cleanup can remove duplication by making the Python checker call the native binary in CI once the build is cheap enough everywhere.