Summary
When you've already identified what command to run in an AI research repo and just need clean execution evidence, this handles the boring parts. It runs your smoke test or documented inference command, captures the output, and writes standardized files to repro_outputs/ with proper success/failure classification. Also generates PATCHES.md when files get modified during execution. The narrow scope is intentional - it won't help you pick targets or set up environments, but it's reliable for the "just run it and document what happened" phase of reproduction work.
Install to Claude Code
npx -y skills add lllllllama/ai-paper-reproduction-skill --skill minimal-run-and-audit --agent claude-codeInstalls into .claude/skills of the current project.
Plug Mailtrap into your AI workflow and let it handle the email.
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Agent, run crypto. Access onchain data & trade routes via 1inch.
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Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
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Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
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Integrate web data into your AI product. One API to scrape website & brand data.
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belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →Files
SKILL.md
Select a file.
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Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →
