cavecrew

JuliusBrussee/caveman · Agent Skill

Three sub-agents for code investigation, editing, and review. They return compressed output, saving context for longer tasks.

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Overview

PublisherJuliusBrusseeCommunity
RepositoryJuliusBrussee/caveman ↗
Skill foldercavecrew
Stars105,532
Forks6,112
Bundled files1
LicenseApache-2.0
Last updatedSeptember 14, 2026
LinksSkill source ↗ · Repository ↗

Mozgi check

What we found in the skill files. Details come with a subscription.

Security
medium risk · 1 point needs attention
Compatibility
instructions only — works with most agents
Similar skills
144 similar skills found
Also with subscription

Installation

A skill is a folder with a SKILL.md file. Pick your agent and run the commands in a terminal (macOS, Linux or Git Bash on Windows) from your project root.

Copy the prompt into Claude, Codex or another assistant: it will review the skill and install it for you.

Install the “cavecrew” skill from mozgi.io (https://mozgi.io/skills/cavecrew/) for me.

1. Download the archive: https://mozgi.io/skills/cavecrew/download
   If it fails, take the skill folder from the source: https://github.com/JuliusBrussee/caveman/tree/main/plugins/caveman/skills/cavecrew
2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me.
3. Put the “cavecrew” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.).
4. Make sure <skills folder>/cavecrew/SKILL.md exists.
5. Briefly tell me what this skill does and offer to try it on my task.

If you cannot do a step yourself, tell me what to click or type.

Review the source files

1 file Download Zip

Read SKILL.md and any companion files before deciding whether to install. Click a file to preview it.

SKILL.md contents

Original author text · read-only

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

| 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 |

| Review diff, branch, or file for bugs | cavecrew-reviewer |

| Deep code review with rationale + alternatives | Code Reviewer (vanilla) |

| 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 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.

Frequently asked questions

What does the cavecrew skill do?

Three sub-agents for code investigation, editing, and review. They return compressed output, saving context for longer tasks.

How do I install cavecrew?

Open the “Installation” block on this page and pick your agent — Claude Code, Codex, Cursor or Gemini CLI — for ready-made commands that copy the skill folder to the right place. Or copy the prompt from the “Via assistant” tab and let the assistant review and install the skill.

Which AI models work with cavecrew?

Skills are plain Markdown instructions (the Agent Skills format), so cavecrew works with any agent that reads SKILL.md: Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and more. The model loads the instructions only when a task matches the skill's description.

Is cavecrew free?

The skill is published openly by JuliusBrussee under the Apache-2.0 license. The skill itself costs nothing — you only pay your AI provider for the tokens you use.

Is it safe to install skills?

A skill is a set of instructions your agent will follow, so read SKILL.md and its companion files before installing. Scripts in the skill folder only run if your agent runs them — keep an eye on what it does and do not grant unnecessary permissions.

How is a skill different from an MCP server or a plugin?

An MCP server or plugin gives the model new tools — code that runs and returns a result. A skill gives it knowledge and process: how to approach a task, which steps to follow and what good output looks like. It needs no server or API key.

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