caveman

Sat, 04 Jul 2026 17:31:19 +0800

JuliusBrussee/caveman

why use many token when few do trick

Make your AI coding agent talk like a caveman.
Same answers, 65% fewer output tokens. Brain still big. Mouth small.

See it · Install · Levels · What you get · Benchmarks · Ecosystem · Caveman 2

Caveman is a skill/plugin for Claude Code, Codex, Gemini, Cursor, Windsurf, Cline, Copilot, and 30+ other agents. Install once. Agent drops the filler and answers in tight caveman-speak, keeping code, commands, and errors byte-for-byte exact. You save output tokens on every reply, forever.

Before / After

🗣️ Normal agent — 69 tokens	Caveman agent — 19 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.	New object ref each render. Inline object prop = new ref = re-render. Wrap in `useMemo`.
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.	Bug in auth middleware. Token expiry check use `<` not `<=`. Fix:

Same fix. Third of the words. Nothing technical lost.

┌────────────────────────────────────────────┐
│   output tokens saved   █████████       65% │
│   input tokens saved    ░░░░░░░░░         0% │
│   technical accuracy    █████████      100% │
│   vibes                 █████████       OOG │
└────────────────────────────────────────────┘

Caveman no make brain smaller. Caveman make mouth smaller. Shrinks what the agent says, not what it knows.

Install

One command. Finds every agent on your machine. Installs for each.

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# macOS · Linux · WSL · Git Bash
curl -fsSL https://raw.githubusercontent.com/JuliusBrussee/caveman/main/install.sh | bash

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2

# Windows · PowerShell 5.1+
irm https://raw.githubusercontent.com/JuliusBrussee/caveman/main/install.ps1 | iex

~30 seconds. Needs Node ≥18. Skips agents you no have. Safe to re-run.

[!TIP] Turn it on: type /caveman or say “talk like caveman”. Turn it off: say “normal mode”. On Claude Code, Codex, and Gemini it’s already on from message one. No command needed.

Install for one agent, or any of 30+ others

Every agent has its own path (plugin, extension, rule file, or npx skills add). The full per-agent matrix, all flags, dry-run, and uninstall live in INSTALL.md. A few common ones:

# Claude Code plugin
claude plugin marketplace add JuliusBrussee/caveman && claude plugin install caveman@caveman

# Gemini CLI extension
gemini extensions install https://github.com/JuliusBrussee/caveman

# Cursor / Windsurf / Cline / Codex / 30+ more, via the skills registry
npx skills add JuliusBrussee/caveman -a cursor

Install broke? Open your agent in this repo and say: “Read CLAUDE.md and INSTALL.md, install caveman for me.” Agent read repo, agent fix own brain. Snake eat tail.

Pick your grunt

Six levels. Switch anytime with /caveman <level>. Level sticks until you change it or the session ends.

Level	Same sentence, shrunk
normal agent	You should wrap the object in `useMemo`, since a new reference is created on every render.
`lite`	Wrap object in `useMemo`. New ref created every render.
`full` (default)	New ref each render. Wrap object in `useMemo`.
`ultra`	New ref/render. `useMemo` it.
`wenyan`	New ref every render, so wrap in `useMemo` — rendered in classical Chinese, shorter still.

[!NOTE] Speak your tongue. Caveman keeps your language. Write Portuguese, caveman grunt Portuguese. Spanish, French, same. It compresses the style, never translates. wenyan mode is the exception on purpose: classical Chinese packs the most meaning per token.

What you get

Command	What it does
`/caveman [lite\|full\|ultra\|wenyan]`	Compress every reply. Level sticks for the session.
`/caveman-commit`	Conventional Commit messages, ≤50-char subject. Why over what.
`/caveman-review`	One-line PR comments: `L42: 🔴 bug: user null. Add guard.`
`/caveman-stats`	Real session token usage, lifetime savings, USD. Tweetable line with `--share`.
`/caveman-compress <file>`	Rewrite a memory file (like `CLAUDE.md`) into caveman-speak. Cuts ~46% input tokens every session after. Code, URLs, paths byte-preserved.
`caveman-shrink`	MCP middleware. Wraps any MCP server, compresses its tool descriptions. npm.
`cavecrew-*`	Caveman subagents (investigator, builder, reviewer). ~60% fewer tokens than vanilla, so main context lasts longer.

[!TIP] On Claude Code the statusline shows [CAVEMAN] ⛏ 12.4k — that’s your lifetime tokens saved, updated on every /caveman-stats. Silence it with CAVEMAN_STATUSLINE_SAVINGS=0.

Benchmarks

Real token counts from the Claude API. Average 65% output reduction across 10 prompts (range 22–87%), measured against default verbose replies. Output tokens only, committed and reproducible in benchmarks/ and evals/.

Task	Normal	Caveman	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%

[!IMPORTANT] Honest number warning. Caveman only shrinks output tokens. Input and reasoning tokens are untouched, and the skill itself adds ~1–1.5k input tokens per turn. So whole-session savings run smaller than the output number, and on already-terse workloads they can go net-negative. The real win is readability and speed. Cost savings are the bonus. When caveman wins, when it loses, and how to measure it yourself: docs/HONEST-NUMBERS.md.

Turns out short isn’t just cheaper. A March 2026 paper, Brevity Constraints Reverse Performance Hierarchies in Language Models, tested 31 models and found that constraining large models to brief answers improved accuracy by ~26 points on some benchmarks. Sometimes less word = more correct.

caveman-compress receipts — real memory files, cutting input tokens forever

File	Original	Compressed	Saved
`claude-md-preferences.md`	706	285	59.6%
`project-notes.md`	1145	535	53.3%
`claude-md-project.md`	1122	636	43.3%
`todo-list.md`	627	388	38.1%
`mixed-with-code.md`	888	560	36.9%
Average	898	481	46%

Every session after, that file loads ~46% smaller. Input tokens saved forever, not just one reply.

The whole cave

Want the whole agent, not just its mouth? → caveman-code

This skill shrinks what an agent says. caveman-code shrinks everything — a full terminal coding agent, caveman top to bottom. ~2× fewer tokens than Codex on identical tasks. 20+ providers, plan mode, autopilot goal loop, MIT.

`1`	`npm install -g @juliusbrussee/caveman-code`

▶ Try caveman-code →

Five tools, one idea: agent do more with less.

Repo	What it shrinks
caveman (you here)	What the agent says
caveman-code	The whole agent, end to end
cavemem	What the agent remembers, across sessions
cavekit	The build loop — spec-driven, no guessing
cavegemma	The compression baked into weights (Gemma fine-tune)

Also: five sibling skills, one install

JuliusBrussee/skills — works in Claude Code, Cursor, Gemini, Cline, Copilot, 40+ agents:

Skill	What
caveman	This one. Speak less, say more.
grill-me	Agent grills your plan before you build the wrong thing.
interface-kit	Build UI that looks good, loads fast, works for everyone.
junior-to-senior	Adversarial review pass. Junior output in, senior output out.
loop-factory	Spec-driven task loop — inbox → active → archive.

`1`	`npx skills@latest add JuliusBrussee/skills`

🦞 Teach the lobster brevity — OpenClaw integration

OpenClaw is a self-host gateway: one box, many agents inside, wired to Slack / Discord / iMessage / Telegram. Lobster strong. Lobster smart. Lobster also talk a lot.

Same installer, scoped to one agent:

`1`	`curl -fsSL https://raw.githubusercontent.com/JuliusBrussee/caveman/main/install.sh \| bash -s -- --only openclaw`

Two things happen, no more: a caveman skill lands in the workspace, and a tiny marker-fenced block is appended to SOUL.md (OpenClaw injects it every turn, so the lobster is terse from message one — no /caveman per session). Custom path? OPENCLAW_WORKSPACE=/your/path. Uninstall with the same line plus --uninstall; your other workspace content stays untouched. Lobster claw still sharp. Lobster mouth now small.

Caveman 2

Caveman make token small. Caveman 2 make it provable.

Today’s savings numbers (including /caveman-stats) are local estimates. Caveman 2 measures and verifies them across a whole team — real receipts, real dashboard, real proof the tokens went down. Building it now.

Join the waitlist → caveman.so

How it works

Install drops a skill file into your agent.
Skill tells agent: drop filler, keep substance, use fragments — but never touch code, commands, or errors.
On Claude Code, a hook writes a tiny flag file each session, so the agent talks caveman from message one without /caveman.
/caveman-stats reads your session log, counts tokens saved, writes the number to your statusline.
/caveman-compress rewrites memory files (like CLAUDE.md) so every future session starts with a smaller context. Save tokens forever, not just once.

Hook architecture, file ownership, and CI sync are documented for maintainers in CLAUDE.md.

Privacy

Caveman no phone home. No telemetry, no analytics, no accounts, no backend. After install, zero network calls — the skill is a prompt, the hooks are local scripts, and /caveman-stats reads a log already on your disk. Install-time fetches (GitHub plus your agents’ own registries) are spelled out in SECURITY.md.

Star this repo

Caveman save you token, save you money. Star cost zero. Fair trade. ⭐

_{Docs:
Install matrix ·
Honest numbers ·
Contributing ·
Maintainer guide ·
Issues

Also by Julius Brussee:
Revu — local-first macOS study app with FSRS spaced repetition (revu.cards)

MIT — free like mass mammoth on open plain.}

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