Repo Intake And Plan
Published by lllllllama in rigorpilot-skills
What this skill does
Scans a repository’s README and common project files to map its structure and find documented commands. It classifies possible inference, evaluation, and training steps, then recommends a minimal reproduction plan without running commands. Best for Researchers and engineers who need to inspect a deep learning repository before choosing what to run.
Add Repo Intake And Plan to your agent
Review the source and files first. When you are ready, copy the prompt instruction or use the CLI command supported by your environment.
Install with a prompt
Paste this into a compatible coding agent:
add this skill "repo-intake-and-plan" from https://github.com/lllllllama/rigorpilot-skillsInstall with the CLI
Run this command in a controlled environment after reviewing the repository:
npx skills add https://github.com/lllllllama/rigorpilot-skills --skill repo-intake-and-planSkill instructions
repo-intake-and-plan
Use this as the Rigor Intake helper. The installed slug remains
repo-intake-and-plan for compatibility.
When to apply
- At the beginning of README-first reproduction work.
- When the main skill needs a fast map of repo structure and documented commands.
- When inference, evaluation, and training candidates must be classified conservatively.
- When the user explicitly wants to inspect the repo first and not run anything yet.
When not to apply
- When execution has already started and the task is now about running commands or writing outputs.
- When the target is not a repository-backed reproduction task.
- When the user only wants paper interpretation without repo inspection.
- When the user already has a selected documented command and only needs setup or execution.
Clear boundaries
- This skill scans and plans.
- This skill is helper-tier and should usually be orchestrator-invoked.
- It does not install environments.
- It does not prepare large assets.
- It does not execute substantive reproduction commands.
- It does not decide high-risk patching.
Input expectations
- Target repository path.
- Access to README and common project files if present.
- Optional user hints about desired priority, such as inference-first.
Output expectations
- concise repo structure summary
- documented command inventory
- inferred candidate categories: inference, evaluation, training, other
- minimum trustworthy reproduction recommendation
- notable ambiguity or risk list
Notes
Use references/repo-scan-rules.md and helper scripts under scripts/.
Files included
- agents/openai.yaml
- references/repo-scan-rules.md
- scripts/extract_commands.py
- scripts/scan_repo.py
- SKILL.md

