When you run a command to reproduce a deep learning result, you need proof. This skill helps you capture that proof in a standardized way. It creates special output files and patch notes so others can see exactly what happened.
The skill works after you already have a plan and a command to run. It does not choose the goal or set up the environment. It just captures the evidence from your run and organizes it into reports.
You will get files like SCIENTIFIC_CHANGELOG.md and COMPARABILITY_REPORT.md. These make your work clear and easy to audit. This is great for anyone who wants to share reproducible research.
Global
mkdir -p ~/.claude/skills/minimal-run-and-auditProject
mkdir -p .claude/skills/minimal-run-and-auditSource Repository
Lark Baselarksuite/cli
Simplify your Lark Base data with tables, fields, records, and views
Lark Wikilarksuite/cli
Manage your Lark Wiki spaces, members, and documents with simple commands
Paper Context Resolverlllllllama/ai-paper-reproduction-skill
Resolve deep learning paper reproduction gaps with precise primary source evidence
Repo Intake And Planlllllllama/ai-paper-reproduction-skill
Scan a repo, extract commands, and get a minimal reproduction plan