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cccskills
무료GitHub에 공개

caveman-explore

Locate relevant code in an unfamiliar repository or after a direct search fails. This read-only explorer returns a short list of file paths, verified line ranges, and relevance notes for another agent to use.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

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.

JuliusBrussee/caveman
설치 방법 보기

이럴 때 유용합니다

  • Find starting points in an unfamiliar codebase
  • Locate logic spread across multiple files
  • Investigate after a direct search fails
  • Hand verified code locations to another agent

포함된 파일(3)

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

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

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.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

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이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

cavecrew

무료

Delegate code lookup, small edits, and diff reviews to three specialized subagents. Their compact, structured results help conserve the main agent's context, with guidance on when to delegate and when to keep work in the main conversation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Locating definitions and callers
  • Making a focused edit across one or two files
  • Reviewing a diff for bugs
JuliusBrussee/caveman11.3만2026년 10월 18일 업데이트

caveman

무료

Make agent replies shorter and easier to scan by putting answers first and removing filler. Preserves technical details, exact commands, numbers, and essential conditions while keeping the user's chosen language.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Reading concise replies in a terminal
  • Getting conclusions before explanations
  • Reducing wording while keeping technical details
JuliusBrussee/caveman11.3만2026년 10월 18일 업데이트

caveman-commit

무료

Create short commit messages using Conventional Commits, a format that labels the type of change. Emphasize intent, keep the subject concise, and include explanatory text when breaking changes, security fixes, data migrations, or reversions require context.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Writing a commit message for code changes
  • Standardizing commit message format
  • Documenting breaking changes and migration steps
JuliusBrussee/caveman11.3만2026년 10월 18일 업데이트

caveman-compress

무료

Compress memory files and task lists into shorter wording to reduce input tokens. Keeps code and document structure intact, saves a readable backup separately, and sends the text to the configured model provider.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Shortening CLAUDE.md to reduce input tokens
  • Compressing task lists and preference files
  • Keeping readable backups of compressed files
JuliusBrussee/caveman11.3만2026년 10월 18일 업데이트

caveman-discover

무료

Find LLM workflows in a codebase and label them by the job they perform, so Caveman Cloud can separate spending by workflow. Present a labeling proposal for approval, apply focused code changes, and check an affected execution path.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Breaking down LLM spending by job
  • Inventorying LLM use in APIs, scheduled jobs, and scripts
  • Separating evaluation spending from other workflows
JuliusBrussee/caveman11.3만2026년 10월 18일 업데이트

caveman-evidence-review

무료

Review Caveman Cloud spending, latency, errors, and potential improvements using current reports and traces, or individual execution records. Produce findings tied to time windows and trace IDs, while keeping measured costs, estimated opportunities, and verified savings separate.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Understanding which workflows drive LLM spending
  • Investigating slow responses and errors
  • Reviewing measured costs and verified savings separately
JuliusBrussee/caveman11.3만2026년 10월 18일 업데이트

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