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Execute a README-first smoke test and produce standardized reproducibility outputs (`repro_outputs/`) and PATCHES.md — trusted reporting for repo reproduction r
Provides a focused execution-and-reporting workflow for README-first AI repos. The skill runs a specified smoke test or documented inference/evaluation command, captures execution evidence, normalizes outputs into a repro_outputs/ directory, and writes patch notes (PATCHES.md) when repository files change during the run. It is intentionally narrow: it does execution/evidence and standardized reporting, not full environment setup or long-running training.
Use after a reproduction target and environment plan already exist and you need a trusted, auditable record of a single run: smoke tests, evaluation commands, or short inference checks. Avoid using it for initial repo scanning, heavy training runs, or when the target is undecided.
scripts/run_command.py and scripts/write_outputs.py (has_scripts=true)references/reporting-policy.md and example reporting templates (has_references=true)repro_outputs/, PATCHES.md).Designed for CI-style automation and developer assistants that perform reproducibility work (agents that can run commands, collect artifacts, and write structured reports).
Cette compétence n'a pas encore été examinée par notre pipeline d'audit automatisé.
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