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cccskills
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caveman-explore

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.

インストール方法を見る

含まれるファイル(3)

  • SKILL.md1.9 KB
  • package.json354 B
  • tests/skill-file.test.mjs2.1 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

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.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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cavecrew

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When to delegate to `cavecrew-investigator` (locate code), `cavecrew-builder` (1-2 file edit) or `cavecrew-reviewer` (diff review) instead of working inline or using `Explore`. Their output is compressed, so main context lasts longer.

日本語の概要は準備中です。原文の説明を表示しています。

JuliusBrussee/caveman11.1万2026年10月11日 更新

caveman

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Terse caveman voice: answer first, fluff gone, every technical fact kept. Use for /caveman, "caveman mode", "talk like caveman", "be brief", "less tokens". Stays on until "stop caveman" or "normal mode".

日本語の概要は準備中です。原文の説明を表示しています。

JuliusBrussee/caveman11.1万2026年10月11日 更新

Write a Conventional Commits message compressed to intent only. Use for "write a commit", "commit message", /commit or /caveman-commit.

日本語の概要は準備中です。原文の説明を表示しています。

JuliusBrussee/caveman11.1万2026年10月11日 更新

Compress a memory file such as CLAUDE.md or a todo list into caveman format to save input tokens, keeping a readable backup. Trigger: /caveman-compress.

日本語の概要は準備中です。原文の説明を表示しています。

JuliusBrussee/caveman11.1万2026年10月11日 更新

Find and label every LLM workflow in the repository so Caveman Cloud groups spend by workflow instead of one bucket. Use for "discover workflows" or breaking LLM spend down by workflow.

日本語の概要は準備中です。原文の説明を表示しています。

JuliusBrussee/caveman11.1万2026年10月11日 更新

Read-only review of Caveman Cloud evidence: cost, Cave Score, workflows, traces, latency, errors, routing, savings. Use when asked what Caveman found or where LLM spend goes.

日本語の概要は準備中です。原文の説明を表示しています。

JuliusBrussee/caveman11.1万2026年10月11日 更新

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