I built analyzerepo to solve the "cold start" problem for both new developers and AI agents. Whether you are jumping into a legacy codebase or trying to make Claude Code actually useful on day one, you usually spend the first hour just trying to figure out where the entry points are and how the pieces fit together.
This is a Go-based CLI that points Claude at any GitHub or local repo to generate three specific, high-context Markdown files:
1) ONBOARDING.md: A human-readable guide that maps out the project’s purpose, language stats, file tree, and a "doc library" of existing .md files. Hand this to a new contributor to save an hour of verbal walkthroughs.
2) ANALYSIS.md: A per-file audit that classifies roles (e.g., entrypoint, core, util) and provides structured improvement suggestions. Each suggestion includes a done_when condition specifically optimized so you can paste the block directly into a Claude Code prompt for a working implementation.
3) CLAUDE.md: A project-specific context file that Claude Code reads automatically to understand your architecture and conventions instead of being generically cautious.
Key Features:
- Zero Dependencies: No runtime or language install required; it’s a single binary.
- Smart Selection: It uses Claude to identify the most structurally significant files instead of hitting token limits with junk files.
- Flexible Backend: It automatically detects your ANTHROPIC_API_KEY or uses your existing Claude CLI installation.
I’d love to hear how this handles your repos or what other "AI-native" documentation formats would be useful for your workflow.
rlnorthcutt•2h ago
This is a Go-based CLI that points Claude at any GitHub or local repo to generate three specific, high-context Markdown files:
1) ONBOARDING.md: A human-readable guide that maps out the project’s purpose, language stats, file tree, and a "doc library" of existing .md files. Hand this to a new contributor to save an hour of verbal walkthroughs.
2) ANALYSIS.md: A per-file audit that classifies roles (e.g., entrypoint, core, util) and provides structured improvement suggestions. Each suggestion includes a done_when condition specifically optimized so you can paste the block directly into a Claude Code prompt for a working implementation.
3) CLAUDE.md: A project-specific context file that Claude Code reads automatically to understand your architecture and conventions instead of being generically cautious.
Key Features:
- Zero Dependencies: No runtime or language install required; it’s a single binary. - Smart Selection: It uses Claude to identify the most structurally significant files instead of hitting token limits with junk files. - Flexible Backend: It automatically detects your ANTHROPIC_API_KEY or uses your existing Claude CLI installation.
I’d love to hear how this handles your repos or what other "AI-native" documentation formats would be useful for your workflow.