analyze-project
lllllllama/rigorpilot-skills
Read-only analysis of deep learning repositories to understand structure, configs, and suspicious patterns.
What is analyze-project?
Analyze-project is a read-only skill for inspecting deep learning research repositories without modifying code or running heavy jobs. Use it to map model architecture, identify training/inference entrypoints, review configurations, and flag implementation concerns before making changes.
- Inspect model structure and architecture
- Identify training and inference entrypoints
- Review configuration files and insertion points
- Flag suspicious implementation patterns
- Generate static analysis reports without code modification
- Map config relationships and dependencies
How to install analyze-project
npx skills add https://github.com/lllllllama/rigorpilot-skills --skill analyze-projectHow to use analyze-project
- 1.Run the skill to perform static analysis of the target repository
- 2.Review the generated SUMMARY.md for repository structure and entrypoints
- 3.Check RISKS.md for flagged suspicious patterns and concerns
- 4.Examine status.json for analysis metadata and findings
- 5.Use insights to plan modifications or understand code flow
Use cases
- Understanding a new deep learning codebase before making modifications
- Reviewing model architecture and training pipeline structure
- Identifying where to insert monitoring or custom logic
- Detecting potential implementation issues or anti-patterns
- Documenting repository structure for team reference
- ML researchers reviewing unfamiliar codebases
- Engineers auditing deep learning implementations
- Teams onboarding to new research projects
- Code reviewers assessing model architecture
- Anyone needing repository analysis without execution risk
analyze-project FAQ
No. This is a read-only skill that performs static analysis only. It does not patch code, execute commands, or run heavy jobs.
It generates three files: SUMMARY.md (repository overview), RISKS.md (flagged patterns and concerns), and status.json (analysis metadata).
Do not use it for debugging tracebacks, environment setup, speculative code adaptation, broad refactoring, or automatic bug fixing.
No. It marks suspicious patterns as heuristics and conservative suggestions, not confirmed bugs.
Yes. It maps config relationships and insertion points, making it useful for planning modifications before implementation.
Full instructions (SKILL.md)
Source of truth, from lllllllama/rigorpilot-skills.
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
../../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.mdanalysis_outputs/RISKS.mdanalysis_outputs/status.json
Notes
Use references/analysis-policy.md and the shared references/research-pitfall-checklist.md.
Related skills
More from lllllllama/rigorpilot-skills and the wider catalog.
ai-research-explore
Auditable deep learning research exploration with idea gating, fair comparison, and governed experiments.
explore-code
Auditable exploratory code modifications for deep learning research on isolated branches with rollback tracking.
ai-research-reproduction
README-first deep learning repository reproduction with auditable evidence and standardized outputs.
paper-context-resolver
Resolve reproduction-critical paper details when README and repo files leave gaps.
safe-debug
Conservative diagnosis and minimal patching for deep learning training failures without automatic code mutation.
run-train
Execute and document deep learning training runs with reproducibility and status tracking.