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$ show JuliusBrussee/caveman

[account ↗] [repo ↗] APPLICATION ★ 107894 6253 ● active (last update 3 weeks ago)
reviewed by: openrouter/owl-alpha

Caveman is a multi-agent AI coding skill/plugin that compresses LLM output tokens by ~65-75% using a 'caveman' terse communication style. It's not a library or service but a distributed configuration package that installs into 30+ AI coding agents (Claude Code, Codex, Gemini, Cursor, Windsurf, Cline, Copilot, opencode, OpenClaw, etc.) through their native plugin/extension/rule-file mechanisms. The core deliverable is a set of SKILL.md prompt files that instruct models to drop articles, filler, pleasantries, and hedging while preserving exact technical substance, code blocks, URLs, and paths. The architecture is a single Node.js installer (bin/install.js) that auto-detects installed agents and dispatches to per-provider installation paths. For Claude Code specifically, it adds SessionStart and UserPromptSubmit hooks plus a statusline badge. The repo includes several sub-skills: caveman-commit (terse conventional commits), caveman-review (one-line PR comments), caveman-compress (rewrites memory files like CLAUDE.md into caveman format to save input tokens), caveman-stats (reads session logs to report real token savings), and cavecrew (compressed subagent definitions for investigator/builder/reviewer patterns). There's also caveman-shrink, an MCP middleware proxy that compresses tool descriptions. The codebase demonstrates strong engineering practices: symlink-safe flag file writes with O_NOFOLLOW and ownership verification, atomic settings.json merges with JSONC tolerance, defensive hook validation before writes, idempotent install/uninstall cycles, and a three-arm eval harness (baseline/terse/skill) for honest token compression measurement. The Python compress tool has safety guards against exfiltrating sensitive files and verifies backup integrity before overwriting. Test coverage is substantial across installer e2e flows, hook symlink safety, opencode plugin lifecycle, and config resolution order.

RATING9.1/10
QUALITY8.3/10
MAINTENANCEactive
DRIFTlow
CONTRIBUTORS29
VELOCITY0.67
OPEN ISSUES136
CLOSED ISSUES87
LAST COMMIT3 weeks ago
Files by Type (count)
Go
645
Other (.mjs)
319
Markdown
179
JSON
163
Python
103
TypeScript
81
Other (.png)
53
JavaScript
50
Other (no ext)
49
YAML
43
Text
16
Other (.svg)
13
Files by Type (size)
Go
6MB
Other (.mjs)
2MB
JSON
2MB
TypeScript
1MB
Other (.png)
1MB
Python
1MB
Markdown
1MB
Other (.gz)
922KB
JavaScript
713KB
YAML
672KB
Other (no ext)
276KB
Other (.woff2)
113KB

The LLM identified 7 files worth highlighting for reuse:

Implements symlink-safe, atomic flag file writes using O_NOFOLLOW and temp+rename patterns, with ownership verification for symlinked parent directories. Also provides a layered config resolution (env var → repo-local .caveman/config.json walking up to root → user XDG config → default). The readFlag function enforces size caps and whitelist validation to prevent injection attacks. This is genuinely reusable defensive filesystem I/O code that solves the common problem of safely writing predictable-path config/flag files in shared or symlinked home directories.

file: src/hooks/caveman-config.js ↗ | tags: #symlink-safe-io #atomic-file-write #config-resolution

A JSONC-tolerant settings.json reader/writer with a hand-rolled state-machine comment stripper that correctly handles comment-looking sequences inside quoted strings. Includes atomic writes (temp + rename), defensive hook field validation that prevents a single malformed entry from poisoning an entire settings file, idempotent add/remove helpers using substring markers, and orphaned-hook pruning. The stripJsonComments function alone is a reusable utility for any tool that needs to read JSONC config files without pulling in a heavy dependency.

file: bin/lib/settings.js ↗ | tags: #jsonc-parser #atomic-write #defensive-validation

A pure-Node prose compressor that mirrors the caveman style rules — dropping articles, filler, pleasantries, hedging, and leaders while preserving protected segments (fenced code, inline code, URLs, paths, CONST_CASE identifiers, dotted.method calls, version numbers). Uses a sentinel-based approach to protect segments during transformation. The compress + compressDescriptionsInPlace API is reusable for any tool that needs to shrink MCP tool descriptions or similar prose fields without breaking technical content.

file: src/mcp-servers/caveman-shrink/compress.js ↗ | tags: #text-compression #protected-segments #mcp-middleware

Orchestrates LLM-based file compression with multiple safety layers: a sensitive-file denylist (credentials, keys, .ssh/.aws paths) that refuses to send content to third-party APIs, backup verification via readback comparison before overwriting the original, YAML frontmatter preservation by surgical split/reassemble, empty/identical output rejection, and a validate-then-targeted-fix retry loop. The safety guard pattern — refusing to process files matching secret/PII heuristics before any API call — is a reusable defensive pattern for any tool that ships file content to external services.

file: skills/caveman-compress/scripts/compress.py ↗ | tags: #llm-orchestration #safety-guards #backup-verification

Validates compressed markdown against originals by checking heading count/order, exact code block preservation (with nested fence support), URL sets, path sets, inline code occurrence counts, and bullet count drift. Returns structured ValidationResult with errors vs warnings. This is a reusable pattern for any lossy text transformation tool that needs to verify structural and content integrity of the output.

file: skills/caveman-compress/scripts/validate.py ↗ | tags: #roundtrip-validation #markdown-parsing #content-integrity

A three-arm eval harness that compares baseline (no system prompt), terse control ('Answer concisely.'), and terse+skill to isolate the skill's actual contribution from the generic terseness effect. Runs real LLM calls per (prompt, arm) and snapshots outputs with metadata. The design insight — measuring skill delta against a terse control rather than baseline — is a genuinely useful pattern for anyone building prompt skills who wants honest efficacy numbers.

file: evals/llm_run.py ↗ | tags: #eval-harness #three-arm-comparison #honest-delta

An ESM Bun plugin that handles dynamic caveman mode tracking for opencode, with a creative cross-runtime module loading solution: it reads the CommonJS caveman-config.js source and evaluates it via new Function() with injected module/exports/require because opencode's compiled Bun binary rejects both require() of on-disk files and await import() of CJS. Also handles opencode's command template expansion (recovering the level argument from expanded template text) and quoted-message unwrapping for non-interactive mode.

file: src/plugins/opencode/plugin.js ↗ | tags: #plugin-architecture #hook-routing #cross-runtime-loading
Last analyzed: 2026-06-30 05:21:47.027933
Next check: 2026-09-26 11:21:00.070097
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