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JuliusBrussee

Cavecrew skill

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.

$npx skills add JuliusBrussee/caveman --skill cavecrew
GitHub stars
118,877
Pack installs
4.8M
Alyn Score
85/99
Updated
3 h ago
License
Apache-2.0

Install Cavecrew

Pick your agent. Every command is ready to paste.

$npx skills add JuliusBrussee/caveman --skill cavecrew

The open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.

01

Install it

Run the command above, or upload the folder in Claude.

02

Ask naturally

Describe the task. Your agent loads cavecrew when the request matches its description.

03

Name it if needed

If it does not trigger, say “use the cavecrew skill”. In Codex, type $cavecrew.

The skill itself

SKILL.md

GitHub

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

Task Use
"Where is X defined / what calls Y / list uses of Z" cavecrew-investigator
Same but you also want suggestions/architecture commentary Explore (vanilla)
Surgical edit, ≤2 files, scope obvious cavecrew-builder
New feature / 3+ files / cross-cutting refactor Main thread, or feature-dev:code-architect if installed
Review diff, branch, or file for bugs cavecrew-reviewer
Deep code review with rationale + alternatives Code Reviewer (vanilla) if installed, else main thread
One-line answer you already know Main 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 accept or reject a subagent's absence claim (No match., No issues., "section missing", "unchanged") without one targeted check of the relevant file, search scope, or diff. Check cited line numbers are within the file before acting.
  • 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.

Tips for Cavecrew

  • • Start a fresh session after installing so your agent picks up the new skill.
  • • It is part of a pack with 22 skills. Install only the ones you need with --skill to keep triggers precise.
  • • If two skills overlap, mention the one you want by name.

Questions about Cavecrew

What does the Cavecrew skill do?

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.

How do I install Cavecrew?

Run "npx skills add JuliusBrussee/caveman --skill cavecrew" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.

Does Cavecrew work in Cursor and Codex?

Yes. Cavecrew uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.

Is Cavecrew free?

Cavecrew is open source on GitHub under the Apache-2.0 license. It is free to install; check the license before commercial use.

Who made Cavecrew?

Cavecrew is published by JuliusBrussee in the JuliusBrussee/caveman repository, together with 21 other skills.

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