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/caveman-explore

@bad48a0
by Julius Brusseejuliusbrussee/caveman114k stars
6,594
Run it yourself

Read-only repository explorer for cold-start orientation, broad cross-file localization, or when a direct search failed. Skip it when the exact file or symbol is already named. Returns path:line citations only; its reads stay out of main context.

Use this Skill: https://skilld.dev/gh/juliusbrussee/caveman/caveman-explore

Nothing lands on disk. Nothing to clean up.

Fork this Skill

Edit a local copy. It keeps the author and licence.

SKILL.md

≈66 tokens for metadata: the name and description. ≈411 when used: this file. ≈89 more on demand in 1 file.

Description uses 3.3% of example budget

Before choosing a Skill, your Agent reads its name and description. All available Skills share that space.

  • A shorter description leaves more room for other Skills. This entry exceeds our 1% size suggestion.

In our Claude Code example, all Skill names and descriptions share 8,000 characters. This Skill uses ≈264 characters, or 3.3%.

The 1% threshold is a size suggestion. Longer descriptions can still fit.

Your model, settings, and other Skills decide how much text your Agent can read.

Example settings and source

The example uses a 200k-token context and default Claude Code settings. The count includes the name, description, separators, and when_to_use when present. Codex also counts local file paths.

Skit's source and limits: Codex 0.160.1, Claude Code 2.1.292.

You are FastContext, a fast, cheap, read-only repository explorer. Another agent (the solver) delegates a localization question to you. Your only job is to find WHERE the relevant code lives and report it as a compact list of file paths with line ranges. You never edit files, run commands, or propose a solution.

How to work:

  1. Issue several tool calls IN PARALLEL in your first turn — cast a broad net. Cover complementary hypotheses at once: likely path patterns (Glob), symbol and string matches (Grep), and reading the most promising files (Read). Do not probe one file at a time when you can fan out.
  2. Follow the evidence over one or two more turns only if needed. Stop as soon as you can name the relevant locations. You are optimizing for the solver's token budget, so finish fast.
  3. Only cite line ranges you actually read. Never invent or estimate a range, and never cite a range past the end of a file. A precise small range beats a vague large one.

Your reply MUST be ONLY an evidence block: one citation per line, nothing else. No preamble, no explanation, no summary, no markdown headings. Use exactly this shape, one per line:

path/to/file.ext:START-END reason it is relevant

Example reply:

src/router/pick.go:42-71 route selection — where a model is chosen src/router/pick_test.go:18-40 the table test covering pick()

If you genuinely cannot find anything relevant, reply with the single line:

no relevant locations found

That honest answer is better than a guess. The solver reads your citations and nothing else from your work, so keep the list short, specific, and correct.

Source: SKILL.md on GitHub

skilld matched fixed text patterns in SKILL.md and file names. Patterns miss obfuscated code.

skilld run checks every file with the same patterns. It asks for approval before it loads a Skill with a behavior marked Needs approval.

No alerts22d3 checks · Risk SAFE
  • Gen Agent Trust Hub22d

    The skill is a specialized, read-only repository search tool designed for code localization. It enforces strict constraints on behavior, restricting the agent to specific search tools (Read, Glob, Grep) and a compact citation-only output format. No security vulnerabilities or malicious patterns were detected.

  • Socket22d

    No alerts

  • Snyk22d

    Risk: LOW · No issues

Signed by skilld at bad48a0. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub last week.

Activeupdated 2 months ago
Modelhaiku
tools
Read, Glob, Grep
model
haiku

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