cavecrew

SkillFiles & storage

Cavecrew cuts your agent's token usage by about 65 percent by rewriting its responses in a compressed, simplified style. Once added, your agent gets its point across with far fewer tokens, which matters most during long coding sessions. It is a skill made for Claude Code.

Available today. Use it from your connected AI after setup.

After adding it, give your agent a coding task and its responses will come back shorter and simpler. Keep working as usual and your token usage should drop by about 65 percent.

Then ask your AI: use the cavecrew skill

What your AI can do with it

  • Cut token usage by about 65 percent
  • Rewrite responses in a compressed, simplified style
  • Shorten replies during coding sessions
  • Keep answers brief and simple

What this skill tells your AI

The instructions your AI receives, as published by juliusbrussee/caveman in skills/cavecrew/SKILL.md and read by ahel’s review.

Cavecrew = three subagent presets that emit caveman output. 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
Review diff, branch, or file for bugscavecrew-reviewer
Deep code review with rationale + alternativesCode Reviewer (vanilla)
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 returns ~700 tokens. 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.
  • 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.

Signals

GitHub stars
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Forks
6k
Last commit
Sep 2026
Installs
298k installs

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Catalog kind
skill
Gateway key
cavecrew
Source
github.com/juliusbrussee/caveman