caveman

why use many token when few do trick

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

A Claude Code skill/plugin and Codex plugin that makes agent talk like caveman — cutting ~75% of tokens while keeping full technical accuracy.

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.

Before / After

🗣️ Normal Claude (69 tokens) "The reason your React component is re-rendering is likely because you're creating a new object reference on each render cycle. When you pass an inline object as a prop, React's shallow comparison sees it as a different object every time, which triggers a re-render. I'd recommend using useMemo to memoize the object."	🪨 Caveman Claude (19 tokens) "New object ref each render. Inline object prop = new ref = re-render. Wrap in `useMemo`."
🗣️ Normal Claude "Sure! I'd be happy to help you with that. The issue you're experiencing is most likely caused by your authentication middleware not properly validating the token expiry. Let me take a look and suggest a fix."	🪨 Caveman Claude "Bug in auth middleware. Token expiry check use `<` not `<=`. Fix:"

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

Sometimes too much caveman. Sometimes not enough:

🪶 Lite

"Your component re-renders because you create a new object reference each render. Inline object props fail shallow comparison every time. Wrap it in useMemo."

🪨 Full

"New object ref each render. Inline object prop = new ref = re-render. Wrap in useMemo."

🔥 Ultra

"Inline obj prop → new ref → re-render. useMemo."

Same answer. You pick how many word.

Benchmarks

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

Task	Normal (tokens)	Caveman (tokens)	Saved
Explain React re-render bug	1180	159	87%
Fix auth middleware token expiry	704	121	83%
Set up PostgreSQL connection pool	2347	380	84%
Explain git rebase vs merge	702	292	58%
Refactor callback to async/await	387	301	22%
Architecture: microservices vs monolith	446	310	30%
Review PR for security issues	678	398	41%
Docker multi-stage build	1042	290	72%
Debug PostgreSQL race condition	1200	232	81%
Implement React error boundary	3454	456	87%
Average	1214	294	65%

Range: 22%–87% savings across prompts.

Important

Caveman only affects output tokens — thinking/reasoning tokens are untouched. Caveman no make brain smaller. Caveman make mouth smaller. Biggest win is readability and speed, cost savings are a bonus.

Science back caveman up

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.

Install

npx skills add JuliusBrussee/caveman

Or with Claude Code plugin system:

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

Codex:

Clone repo
Open Codex in repo
Run /plugins
Search Caveman
Install plugin

Install once. Use in all sessions after that.

One rock. That it.

Usage

Trigger with:

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

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

Intensity Levels

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

Level	Trigger	What it do
Lite	`/caveman lite` or `$caveman lite`	Drop filler, keep grammar. Professional but no fluff
Full	`/caveman full` or `$caveman full`	Default caveman. Drop articles, fragments, full grunt
Ultra	`/caveman ultra` or `$caveman ultra`	Maximum compression. Telegraphic. Abbreviate everything

Level stick until you change it or session end.

What Caveman Do

Thing	Caveman Do?
English explanation	🪨 Caveman smash filler words
Code blocks	✍️ Write normal (caveman not stupid)
Technical terms	🧠 Keep exact (polymorphism stay polymorphism)
Error messages	📋 Quote exact
Git commits & PRs	✍️ Write normal
Articles (a, an, the)	💀 Gone
Pleasantries	💀 "Sure I'd be happy to" is dead
Hedging	💀 "It might be worth considering" extinct

Why

┌─────────────────────────────────────┐
│  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

How It Work

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.

Star This Repo

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

Also by Julius Brussee

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

License

MIT — free like mass mammoth on open plain.

Caveman: Why use many token when few token do trick