repo-surveyor
Use when Cartograph CLI or MCP is unavailable and you still need Cartograph-style repo orientation, task context, or documentation inputs from manual file survey.
Best use case
repo-surveyor is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when Cartograph CLI or MCP is unavailable and you still need Cartograph-style repo orientation, task context, or documentation inputs from manual file survey.
Teams using repo-surveyor should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/repo-surveyor/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How repo-surveyor Compares
| Feature / Agent | repo-surveyor | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when Cartograph CLI or MCP is unavailable and you still need Cartograph-style repo orientation, task context, or documentation inputs from manual file survey.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
Use this skill only when Cartograph itself is unavailable or when you need to manually verify its outputs. Manual workflow: 1. Discover source, config, and entry files. Skip generated, vendored, and build output. 2. Rank likely-important files by entry points, fan-in, API surface, and root wiring role. 3. Trace the strongest dependency hubs instead of reading the whole tree. 4. Build the smallest useful file set for the current task. 5. Produce a doc-ready summary from that reduced set. Output contract: - Key files - Dependency hubs - Minimal task context - Doc-ready summary Rules: - If the OpenProse plugin is enabled, start from the bundled templates in `openprose/`. - Prefer `use-cartograph` whenever the tool becomes available. - Keep manual reads narrow. - Match the same output shape as `use-cartograph`.
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