cavecrew
🤖 AI Summary
**`cavecrew`** provides three subagent presets (investigator, builder, reviewer) that perform the same tasks as Anthropic's default agents but compress tool results, reducing main context consumption with each delegation. Use it for targeted code investigation, surgical edits, or bug reviews where minimizing context overhead is critical.
How to Install
Claude Code:
git clone --depth 1 https://github.com/JuliusBrussee/caveman.git && cp caveman/skills/cavecrew ~/.claude/skills/cavecrew -rCavecrew = 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`**
```
:
- path:line — `symbol` — short note
totals: .
```
Or `No match.` Always file-path-first, line-number-attached, backticked symbols. Safe to grep with `path:\d+`.
**`cavecrew-builder`**
```
— .
verified: .
```
Or one of: `too-big.` / `needs-confirm.` / `ambiguous.` / `regressed.` (terminal first token).
**`cavecrew-reviewer`**
```
path:line: : . .
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, so
Details
| Category | Coding → generation |
| Source | JuliusBrussee/caveman |
| SKILL.md | View on GitHub → |
| Repo Stars | ★ 76.2K |
| Est. per Skill | ~10.9K (shared across 7 skills from this repo) |
| Difficulty | Intermediate |
| Risk Level | N/A |
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