cavecrew

Delegates code investigation, editing, and review to compressed-output subagents.

1|Updated Aug 24, 2026
One-click install
npx skills add https://github.com/CliffVale/opencode-free-setup --skill cavecrew-cliffvale
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cavecrew
Source: https://github.com/CliffVale/opencode-free-setup/tree/main/skills/cavecrew
Command: npx skills add https://github.com/CliffVale/opencode-free-setup --skill cavecrew-cliffvale

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Subagent results are injected verbatim into the main conversation context, so verbose agent output quickly exhausts the context window during long coding sessions. This Skill decides when to delegate work to caveman-compressed subagents so each delegation costs roughly 60% fewer tokens. ## Core Features & Use Cases - Delegation decision guide: Maps task types to the right agent — cavecrew-investigator for locating code, cavecrew-builder for 1-2 file edits, cavecrew-reviewer for diff audits — versus vanilla agents or the main thread. - Structured output contracts: Defines predictable, grep-friendly result formats (path:line findings, verified edit confirmations, severity-tagged review findings) the main thread can rely on. - Chaining patterns: Documents locate → fix → verify pipelines, parallel investigator scouting, and single-shot edits for known sites. - Use Case: During a long refactoring session, spawn cavecrew-investigator to find all callers of a function, hand the top site to cavecrew-builder for the edit, then have cavecrew-reviewer audit the diff — all while keeping main-context usage low. ## Quick Start Ask the agent to use cavecrew to locate where a function is defined, apply a small edit, and review the resulting diff with compressed subagent output.

Frequently Asked Questions about cavecrew

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

FAQPage Schema
How do I reduce context usage when delegating to AI coding subagents?▼

Delegate to subagents that return compressed, structured output instead of prose. Cavecrew's investigator, builder, and reviewer agents return roughly 60% smaller tool results, so each delegation consumes far less of the main context window.

When should I use cavecrew-investigator instead of the vanilla Explore agent?▼

Use cavecrew-investigator for pure location tasks like finding definitions, callers, or usages, where you want file-path-first, line-numbered results. Choose vanilla Explore when you also want suggestions or architecture commentary in prose.

What tasks should not be delegated to cavecrew-builder?▼

Do not use cavecrew-builder for new features, edits spanning three or more files, or cross-cutting refactors — it returns `too-big.` for those. It handles surgical edits of one to two files where the scope is already known.

Can cavecrew-reviewer replace a full code review agent?▼

No. cavecrew-reviewer returns only severity-tagged findings sorted by file and line, with no rationale or architecture opinions. For deep reviews with reasoning and alternatives, use the vanilla Code Reviewer agent instead.

Why does cavecrew output look terse or cryptic?▼

Cavecrew agents emit caveman-compressed structured output by design to minimize token cost when injected into main context. They automatically switch to normal English for security warnings, irreversible-action confirmations, and ambiguous cases.