cavecrew

Guides delegation to compressed-output subagents for code location, editing, and review tasks.

Updated Mar 30, 2026
One-click install
npx skills add https://github.com/TrayMachi/dotfiles --skill cavecrew-traymachi
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cavecrew
Source: https://github.com/TrayMachi/dotfiles/tree/main/agents/skills/cavecrew
Command: npx skills add https://github.com/TrayMachi/dotfiles --skill cavecrew-traymachi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Long coding sessions exhaust the main agent's context window because every subagent result is injected back verbatim, and verbose prose output burns through the budget quickly. This Skill provides a decision guide for when to delegate work to caveman-compressed subagents instead of doing work inline, cutting injected output to roughly one third of vanilla size. ## Core Features & Use Cases - Delegation Decision Matrix: Maps task types to the right agent — cavecrew-investigator for locating code, cavecrew-builder for surgical 1-2 file edits, cavecrew-reviewer for diff audits, or vanilla agents when prose and rationale are wanted. - Output Contracts: Defines exact structured formats each subagent returns (path:line findings, verified edit confirmations, severity-tagged review findings) so the main thread can parse results reliably. - Chaining Patterns: Documents workflows like locate → fix → verify and parallel scouting with multiple investigators. - Use Case: During a long refactoring session, spawn cavecrew-investigator to find all call sites of a function, hand the top two paths to cavecrew-builder for the edit, then have cavecrew-reviewer audit the diff — all while keeping main-context usage minimal. ## Quick Start Ask the agent to delegate a code search to the cavecrew investigator instead of running the exploration inline to save context.

Frequently Asked Questions about cavecrew

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I delegate code search to a subagent to save context?

Spawn cavecrew-investigator with a locate-style query such as finding a definition or listing callers. It returns compressed path:line findings with backticked symbols, roughly one third the size of vanilla Explore output, preserving main-context budget.

When should I use cavecrew-builder versus editing in the main thread?

Use cavecrew-builder for surgical edits of one to two files where the scope is already obvious. For three or more files, cross-cutting refactors, or new features, use the main thread or a feature architect agent, since the builder refuses oversized scope with a too-big response.

What is the difference between cavecrew-reviewer and a vanilla code reviewer?

cavecrew-reviewer returns one-line findings with severity emoji sorted by file and line, with no architecture commentary. The vanilla Code Reviewer provides prose, rationale, and alternatives, which costs more context but suits deep reviews.

Can I run multiple investigator subagents in parallel?

Yes, the parallel scout pattern spawns two to three cavecrew-investigator calls in one message with different angles such as definitions, callers, and tests. The main thread then aggregates the compressed results.

When should I not use cavecrew subagents?

Avoid cavecrew when you want prose, architecture opinions, or rationale, when the answer is a one-liner you already know, or when a human will read the output directly. The terse structured format can be cryptic without paraphrasing.