ai-research-explore
Rigor Explore compatible skill slug for meaningful and potentially novel deep learning research candidates. Use when the…
@lllllllamaInstall SkillDevelopment
Skill
/analyze-project
Rigor Analyze / Rigor Audit read-only skill for deep learning research repositories. Use when the user wants to read and understand a repository, inspect model structure and training or inference entrypoints, review configs and insertion points, or flag suspicious implementation
Claude Code
$ npx -y skills add lllllllama/rigorpilot-skills --skill analyze-project --agent claude-code
Codex
$ npx skills add lllllllama/rigorpilot-skills --skill analyze-project -a codex -y
Cursor
$ npx skills add lllllllama/rigorpilot-skills --skill analyze-project -a cursor -y
Gemini CLI
$ npx skills add lllllllama/rigorpilot-skills --skill analyze-project -a gemini-cli -y
GitHub Copilot
$ npx skills add lllllllama/rigorpilot-skills --skill analyze-project -a github-copilot -y
OpenCode
$ npx skills add lllllllama/rigorpilot-skills --skill analyze-project -a opencode -y
Windsurf
$ npx skills add lllllllama/rigorpilot-skills --skill analyze-project -a windsurf -y
SKILL.md
analyze-project.SKILL.mdname: analyze-project
description: Rigor Analyze / Rigor Audit read-only skill for deep learning research repositories. Use when the user wants to read and understand a repository, inspect model structure and training or inference entrypoints, review configs and insertion points, or flag suspicious implementation patterns without modifying code or running heavy jobs. Do not use for active command execution, broad refactoring, speculative code adaptation, or automatic bug fixing.
analyze-project
Use this as the Rigor Analyze / Rigor Audit read-only skill. The installed slug remains `analyze-project` for compatibility.
Use the shared operating principles in `../ai-research-reproduction/references/agent-operating-principles.md`; this skill should guide read-only analysis without constraining the model's project-specific reasoning.
When to apply
- The user wants to understand a deep learning repository before changing it.
- The user needs a map of model structure, training entrypoints, inference entrypoints, and config relationships.
- The user wants conservative suggestions about likely insertion points or suspicious implementation patterns.
- The user explicitly wants read-only analysis and not heavy execution.
When not to apply
- When the main task is to execute a failing command or debug a traceback.
- When the user wants environment setup or asset download only.
- When the user wants speculative adaptation or broad exploratory patching.
- When the task is a general literature summary without repository analysis.
Clear boundaries
- This skill is read-mostly.
- It may run lightweight static inspection helpers.
- It does not patch repository code.
- It does not own final reproduction outputs.
- It should mark suspicious patterns as heuristics, not confirmed bugs.
Output expectations
- `analysis_outputs/SUMMARY.md`
- `analysis_outputs/RISKS.md`
- `analysis_outputs/status.json`
Notes
Use `references/analysis-policy.md` and the shared `../ai-research-reproduction/references/research-pitfall-checklist.md`.
Read more
name: analyze-project description: Rigor Analyze / Rigor Audit read-only skill for deep learning research repositories. Use when the user wants to read and understand a repository, inspect model structure and training or inference entrypoints, review configs and insertion points, or flag suspicious implementation patterns without modifying code or running heavy jobs. Do not use for active command execution, broad refactoring, speculative code adaptation, or automatic bug fixing.
analyze-project
Use this as the Rigor Analyze / Rigor Audit read-only skill. The installed slug remains `analyze-project` for compatibility.
Use the shared operating principles in `../ai-research-reproduction/references/agent-operating-principles.md`; this skill should guide read-only analysis without constraining the model's project-specific reasoning.
When to apply
- The user wants to understand a deep learning repository before changing it.
- The user needs a map of model structure, training entrypoints, inference entrypoints, and config relationships.
- The user wants conservative suggestions about likely insertion points or suspicious implementation patterns.
- The user explicitly wants read-only analysis and not heavy execution.
When not to apply
- When the main task is to execute a failing command or debug a traceback.
- When the user wants environment setup or asset download only.
- When the user wants speculative adaptation or broad exploratory patching.
- When the task is a general literature summary without repository analysis.
Clear boundaries
- This skill is read-mostly.
- It may run lightweight static inspection helpers.
- It does not patch repository code.
- It does not own final reproduction outputs.
- It should mark suspicious patterns as heuristics, not confirmed bugs.
Output expectations
- `analysis_outputs/SUMMARY.md`
- `analysis_outputs/RISKS.md`
- `analysis_outputs/status.json`
Notes
Use `references/analysis-policy.md` and the shared `../ai-research-reproduction/references/research-pitfall-checklist.md`.
Stats
486
Stars
20
Forks
Maintained
Maintenance
Python
Language
MIT
License
Last commit
Created
Ships withrigorpilot-skills
Run research repositories from their README, with bounded execution and auditable evidence. RigorPilot adds section-level results without rewriting the original README. Trusted reproduction is the default; candidate exploration requires explicit authorization.
48611 skills
Stars on GitHub
Momentum
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- 486
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Questions about analyze-project.
- Which coding agents can use analyze-project?
- analyze-project installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.