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cccskills
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cavecrew

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.

원문원문 설명 보기

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.

설치 방법 보기

이럴 때 유용합니다

  • Locating definitions and callers
  • Making a focused edit across one or two files
  • Reviewing a diff for bugs
  • Chaining code lookup, editing, and review

포함된 파일(2)

  • SKILL.md3.7 KB
  • README.md2.8 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Cavecrew = three subagent presets that answer in ultracave voice (tool runs: one status line in, one out; nothing between routine calls). Same job as Anthropic defaults (Explore, edit-style agents, reviewer); difference is the tool-result they return is compressed, so main context shrinks per delegation.

When to use cavecrew vs alternatives

TaskUse
"Where is X defined / what calls Y / list uses of Z"cavecrew-investigator
Same but you also want suggestions/architecture commentaryExplore (vanilla)
Surgical edit, ≤2 files, scope obviouscavecrew-builder
New feature / 3+ files / cross-cutting refactorMain thread, or feature-dev:code-architect if installed
Review diff, branch, or file for bugscavecrew-reviewer
Deep code review with rationale + alternativesCode Reviewer (vanilla) if installed, else main thread
One-line answer you already knowMain thread, no subagent

Rule of thumb: if you'd want the subagent's output in 1/3 the tokens, pick cavecrew. If you'd want prose, pick vanilla.

Why this exists (the real win)

Subagent tool results get injected into main context verbatim. A vanilla Explore that returns 2k tokens of prose costs 2k tokens of main-context budget every time. The same finding from cavecrew-investigator comes back as a compressed path:line table instead. Across 20 delegations in one session that's the difference between context exhaustion and finishing the task.

Output contracts

What main thread can rely on per agent:

cavecrew-investigator

<Header>:
- path:line — `symbol` — short note
totals: <counts>.

Or No match. Always file-path-first, line-number-attached, backticked symbols. Safe to grep with path:\d+.

cavecrew-builder

<path:line-range> — <change ≤10 words>.
verified: <re-read OK | mismatch @ path:line>.

Or one of: too-big. / needs-confirm. / ambiguous. / regressed. (terminal first token).

cavecrew-reviewer

path:line: <emoji> <severity>: <problem>. <fix>.
totals: N🔴 N🟡 N🔵 N❓

Or No issues. Findings sorted file → line ascending.

Chaining patterns

Locate → fix → verify (most common):

  1. cavecrew-investigator returns site list.
  2. Main thread picks 1-2 sites, hands paths to cavecrew-builder.
  3. cavecrew-reviewer audits the diff.

Parallel scout (when investigation is broad): Spawn 2-3 cavecrew-investigator calls in one message (different angles: defs vs callers vs tests). Aggregate in main thread.

Single-shot edit (when site is already known): Skip investigator. Hand exact path:line to cavecrew-builder directly.

What NOT to do

  • Don't use cavecrew-builder when you don't already know the file. Spawn investigator first or main thread will eat tokens passing context.
  • Don't chain cavecrew-investigator → cavecrew-builder for a 5-file refactor. Builder will return too-big. and you'll have wasted a turn.
  • Don't ask cavecrew-reviewer for "general feedback" — it returns findings only, no architecture opinions. Use Code Reviewer for that when installed.
  • Don't expect prose. Cavecrew output is structured, sometimes terse to the point of cryptic. If a human will read it directly, paraphrase.

Auto-clarity (inherited)

Subagents drop caveman → normal English for security warnings, irreversible-action confirmations, and any output where fragment ambiguity could be misread. Resume caveman after.

리뷰

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같은 저장소의 스킬

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
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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

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
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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
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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
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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.

  • Find starting points in an unfamiliar codebase
  • Locate logic spread across multiple files
  • Investigate after a direct search fails
JuliusBrussee/caveman11.3만2026년 10월 18일 업데이트

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