Minimal Run And Audit
Skill Verified ActiveTrusted-lane execution and reporting skill for README-first AI repo reproduction. Use when the task is specifically to capture or normalize evidence from the selected smoke test or documented inference or evaluation command and write standardized `repro_outputs/` files, including patch notes when repository files changed. Do not use for training execution, initial repo intake, generic environment setup, paper lookup, target selection, or end-to-end orchestration by itself.
To provide a trusted and auditable way to execute and report on documented commands in AI research repositories, ensuring evidence is captured consistently for reproduction.
Features
- Trusted execution lane for AI repo reproduction
- Captures command output, errors, and file changes
- Generates standardized `repro_outputs/` files
- Handles execution timeouts and non-zero exit codes
- Supports patch notes when repository files change
Use Cases
- Verifying documented inference or evaluation commands
- Capturing evidence from smoke tests
- Normalizing execution results for auditability
- Reporting on repository file changes after command execution
Non-Goals
- Initial repo scanning or intake
- Generic environment setup
- Paper lookup or target selection
- End-to-end orchestration by itself
- Training execution or state management
Installation
npx skills add lllllllama/ai-paper-reproduction-skillRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedSimilar Extensions
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Ops Revenue
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