repo-analysis
Techniques for deep-diving into unknown codebases. Focuses on dependency graphs, data flow, and architectural patterns. Use when starting a task in an unfamiliar project.
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View on GitHubSKILL.mdskills/repo-analysis/SKILL.md
GitHubRepository Analysis
Purpose
Rapidly gain a comprehensive understanding of a project's architecture, dependencies, and internal logic.
When to Use This Skill
Use during the first 15 minutes of any task in a project that has not been previously analyzed.
Phase 1: Structural Audit
- Map the directory structure: Use the
list_dirormcp_filesystem_directory_treetools. Do not uselsvia bash. - Identify core technologies: Read
package.json,requirements.txt, etc., usingmcp_filesystem_read_text_file.
Phase 2: Logic Flow Analysis
- Trace entry points: Use
grep_searchto mapimporttrees and function calls. Never usegrepinside a bash command. - Monorepo Scale Analysis: For massive monolithic repositories, avoid raw exhaustive grep. Use AST (Abstract Syntax Tree) parsing or vector-based codebase search if available to prevent context limit exhaustion.
- Data Model Discovery: Identify the main data models and state management strategy.
- Did I identify the true root cause, or just a symptom?
- Is the proposed change isolated, or will it break upstream logic?
Output Format / Delivery
- A concise context mapping report.
- A targeted execution plan for fixes.
Behavior Rules
- Trust but Verify. Do not rely on outdated READMEs; check the actual code.
- Document Findings. Save a summary of the project's "mental model" in artifacts.
Maintenance Notes
- Initial global core skill.