---
id: gh-cavecrew
name: "cavecrew"
url: https://skills.yangsir.net/skill/gh-cavecrew
author: juliusbrussee
domain: ai-llm-engineering
tags: ["llm-optimization", "code-analysis", "token-efficiency", "subagent", "developer-tools"]
install_count: 193400
rating: 4.80 (120 reviews)
github: https://github.com/juliusbrussee/caveman/tree/main/skills/cavecrew
---

# cavecrew

> Cavecrew 是一组子代理预设，通过压缩输出，显著减少 Anthropic 默认代理的上下文令牌消耗。它提供调查、构建和审查三种模式，适用于代码定位、小范围修改和缺陷检查，帮助用户在多轮对话中避免上下文耗尽，提高开发效率。

**Stats**: 193,400 installs · 4.8/5 (120 reviews)

## Before / After 对比

### 令牌消耗优化

**Before**:

使用 Anthropic 默认的 `Explore` 子代理进行代码调查时，其详细的散文式输出会消耗大量上下文令牌，每次操作可能占用 2000 令牌，导致多轮对话后上下文迅速耗尽。

**After**:

使用 `cavecrew-investigator` 子代理进行相同的代码调查，其压缩和结构化的输出将令牌消耗降低至约 700 令牌，显著延长了上下文寿命，使多轮复杂任务得以顺利完成。

| Metric | Before | After | Change |
|---|---|---|---|
| 令牌消耗 | 2000令牌 | 700令牌 | -65% |

## Readme

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.


---
*Source: https://skills.yangsir.net/skill/gh-cavecrew*
*Markdown mirror: https://skills.yangsir.net/api/skill/gh-cavecrew/markdown*