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cavecrew

Delegate code lookup, small edits, and diff reviews to three specialized subagents. Their compact, structured results help conserve the main agent's context, with guidance on when to delegate and when to keep work in the main conversation.

OriginalShow the original description

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.

AI rating90/ 100See how to install

Good for

  • Locating definitions and callers
  • Making a focused edit across one or two files
  • Reviewing a diff for bugs
  • Chaining code lookup, editing, and review

Overview

What it does

Routes code lookup, focused edits, and diff reviews to three specialized subagents. cavecrew-investigator locates definitions and callers, cavecrew-builder edits one or two files, and cavecrew-reviewer identifies bugs. Results use compact formats, including file paths and line numbers, to reduce the context the main agent needs to retain.

When it helps

Use it during development that involves repeated investigation and small changes. You can connect the steps: locate the relevant code, make a focused edit, then review the diff. It also provides guidance for choosing between these subagents, standard Explore, and the main conversation according to the work involved.

Example requests

  • “Find this function’s definition and the places that call it.”
  • “Fix the relevant section in the specified file.”
  • “Review this diff for bugs.”

Notes

The editing subagent is intended for tasks with clearly identified files and scope, covering no more than two files. Handle new features and larger changes spanning multiple areas in the main conversation or another suitable workflow. Replies are brief and structured; use another approach for detailed design explanations or discussions of alternatives.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodThe document assigns code lookup, edits within two files, and bug review to specific agents and explains when to choose each.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
AGoodIt provides a lookup, edit, and review sequence and defines each agent’s output format with paths and line numbers.
SafetyAre sending data, deleting files, and running commands disclosed?
AGoodEdits are limited to clearly scoped work within two files, and irreversible actions require confirmation in normal prose.
Easy setupDoes it need few tools or API keys, and are they documented?
BPartly lackingIt uses three subagent presets but does not explain how to install them.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 20, 2026. Treat it as a guide and read the original before installing.

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Files included (2)

  • SKILL.md3.7 KB
  • README.md2.8 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Cavecrew = three subagent presets that answer in ultracave voice (tool runs: one status line in, one out; nothing between routine calls). 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

TaskUse
"Where is X defined / what calls Y / list uses of Z"cavecrew-investigator
Same but you also want suggestions/architecture commentaryExplore (vanilla)
Surgical edit, ≤2 files, scope obviouscavecrew-builder
New feature / 3+ files / cross-cutting refactorMain thread, or feature-dev:code-architect if installed
Review diff, branch, or file for bugscavecrew-reviewer
Deep code review with rationale + alternativesCode Reviewer (vanilla) if installed, else main thread
One-line answer you already knowMain 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 comes back as a compressed path:line table instead. 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 when installed.
  • 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.

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