/install cavecrew
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
\x3CHeader>:
- path:line — `symbol` — short note
totals: \x3Ccounts>.
Or No match. Always file-path-first, line-number-attached, backticked symbols. Safe to grep with path:\d+.
cavecrew-builder
\x3Cpath:line-range> — \x3Cchange ≤10 words>.
verified: \x3Cre-read OK | mismatch @ path:line>.
Or one of: too-big. / needs-confirm. / ambiguous. / regressed. (terminal first token).
cavecrew-reviewer
path:line: \x3Cemoji> \x3Cseverity>: \x3Cproblem>. \x3Cfix>.
totals: N🔴 N🟡 N🔵 N❓
Or No issues. Findings sorted file → line ascending.
Chaining patterns
Locate → fix → verify (most common):
cavecrew-investigatorreturns site list.- Main thread picks 1-2 sites, hands paths to
cavecrew-builder. cavecrew-revieweraudits 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-builderwhen you don't already know the file. Spawn investigator first or main thread will eat tokens passing context. - Don't chain
cavecrew-investigator → cavecrew-builderfor a 5-file refactor. Builder will returntoo-big.and you'll have wasted a turn. - Don't ask
cavecrew-reviewerfor "general feedback" — it returns findings only, no architecture opinions. UseCode Reviewerfor 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.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install cavecrew - 安装完成后,直接呼叫该 Skill 的名称或使用
/cavecrew触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Cavecrew 是什么?
Decision guide for delegating to caveman-style subagents. Tells the main thread WHEN to spawn `cavecrew-investigator` (locate code), `cavecrew-builder` (1-2... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 16 次。
如何安装 Cavecrew?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install cavecrew」即可一键安装,无需额外配置。
Cavecrew 是免费的吗?
是的,Cavecrew 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Cavecrew 支持哪些平台?
Cavecrew 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Cavecrew?
由 Sean Ford(@seanford)开发并维护,当前版本 v1.0.0。