caveman

why use many token when few do trick

Install • Benchmarks • Before/After • Intensity Levels • Compress • Why

A Claude Code skill/plugin and Codex plugin that makes agent talk like caveman — cutting ~75% of output tokens while keeping full technical accuracy. Plus a companion tool that compresses your memory files to cut ~45% of input tokens every session.

Based on the viral observation that caveman-speak dramatically reduces LLM token usage without losing technical substance. So we made it a one-line install.

Same fix. 75% less word. Brain still big.

Sometimes too much caveman. Sometimes not enough:

Same answer. You pick how many word.

Real token counts from the Claude API (reproduce it yourself):

Range: 22%–87% savings across prompts.

A March 2026 paper "Brevity Constraints Reverse Performance Hierarchies in Language Models" found that constraining large models to brief responses improved accuracy by 26 percentage points on certain benchmarks and completely reversed performance hierarchies. Verbose not always better. Sometimes less word = more correct.

npx skills add JuliusBrussee/caveman

npx skills supports 40+ agents — Claude Code, GitHub Copilot, Cursor, Windsurf, Cline, and more. To install for a specific agent:

npx skills add JuliusBrussee/caveman -a cursor
npx skills add JuliusBrussee/caveman -a copilot
npx skills add JuliusBrussee/caveman -a cline
npx skills add JuliusBrussee/caveman -a windsurf

Or with Claude Code plugin system:

claude plugin marketplace add JuliusBrussee/caveman
claude plugin install caveman@caveman

Codex:

1. Clone repo
2. Open Codex in repo
3. Run /plugins
4. Search Caveman
5. Install plugin

Install once. Use in all sessions after that.

One rock. That it.

Trigger with:

• /caveman or Codex $caveman
• "talk like caveman"
• "caveman mode"
• "less tokens please"

Stop with: "stop caveman" or "normal mode"

Sometimes full caveman too much. Sometimes not enough. Now you pick:

Level stick until you change it or session end.

┌─────────────────────────────────────┐
│  TOKENS SAVED          ████████ 75% │
│  TECHNICAL ACCURACY    ████████ 100%│
│  SPEED INCREASE        ████████ ~3x │
│  VIBES                 ████████ OOG │
└─────────────────────────────────────┘

• Faster response — less token to generate = speed go brrr
• Easier to read — no wall of text, just the answer
• Same accuracy — all technical info kept, only fluff removed (science say so)
• Save money — ~71% less output token = less cost
• Fun — every code review become comedy

Caveman not dumb. Caveman efficient.

Normal LLM waste token on:

• "I'd be happy to help you with that" (8 wasted tokens)
• "The reason this is happening is because" (7 wasted tokens)
• "I would recommend that you consider" (7 wasted tokens)
• "Sure, let me take a look at that for you" (10 wasted tokens)

Caveman say what need saying. Then stop.

Caveman makes Claude speak with fewer tokens. Caveman Compress makes Claude read fewer tokens.

Your CLAUDE.md loads on every session start. A 1000-token project memory file costs you tokens every single time you open a project. Caveman Compress rewrites those files into caveman-speak so Claude reads less — without you losing the human-readable original.

/caveman-compress CLAUDE.md

CLAUDE.md          ← compressed (Claude reads this every session — fewer tokens)
CLAUDE.original.md ← human-readable backup (you read and edit this)

A Python pipeline that shells out to claude --print for the actual compression, then validates the result locally — no tokens wasted on checking.

detect file type (local)  →  compress with Claude (1 call)  →  validate (local)
                                                                    ↓
                                                              if errors: targeted fix (1 call, cherry-pick only)
                                                                    ↓
                                                              retry up to 2×, restore original on failure

Code blocks, inline code, URLs, file paths, commands, headings, table structure, dates, version numbers — anything technical passes through untouched. Only natural language prose gets compressed.

See the full caveman-compress README for install, usage, and validation details.

If caveman save you mass token, mass money — leave mass star. ⭐

• Blueprint — specification-driven development for Claude Code. Natural language → blueprints → parallel builds → working software.
• Revu — local-first macOS study app with FSRS spaced repetition, decks, exams, and study guides. revu.cards

MIT — free like mass mammoth on open plain.