# cavecrew

> Claude/Codex skill by [@juliusbrussee](https://omgskills.com/library/juliusbrussee/index.md) · 120k stars · 378k installs · Updated 2026-11-13

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.

Tags: ai, anthropic, caveman, claude, claude-code, llm, meme, prompt-engineering, skill, tokens

## Install

```sh
git clone https://github.com/JuliusBrussee/caveman /tmp/caveman && ln -s /tmp/caveman/skills/cavecrew ~/.claude/skills/cavecrew
```

## From README

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.

## Links

- HTML page: https://omgskills.com/library/juliusbrussee/caveman/cavecrew/
- GitHub: https://github.com/JuliusBrussee/caveman
- Author: [@juliusbrussee](https://omgskills.com/library/juliusbrussee/index.md)

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