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Normal agent · 63 tokens	Caveman agent · 20 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, so React re-renders. Wrap the prop in useMemo.

Same fix. 63 token become 20. Brain still big.

Pick your club:

Skill	Same answer	Tokens
/caveman	New object ref each render, so React re-renders. Wrap the prop in useMemo.	20
/ultracave	Inline object prop, new ref, re-render. useMemo.	14
/megacave	新參照致重繪。useMemo。	13

_{Token counts: tiktoken o200k.}

Install

npx @caveman-ai/cli@latest

One command. Mac, Linux, Windows. Caveman find your agents and your logins, show what it change. Press Enter. Done. Needs Node.js 22.13+.

After that, plain claude stays caveman'd. So do Codex, Gemini CLI, OpenCode, and 30+ more. It runs on your machine, with your keys and your Claude Pro/Max login. One rock. That it.

_{Had caveman before 4.0? Say @latest, or the old copy on your machine wins. Already set up? caveman setup opens the screen again. Only want shorter answers? Get just the skill.}

Six rocks, one install

New in 4.0: caveman is six parts. All on after install. Each has its own switch.

Rock	What it does	Measured
Say less	Agent answers short. Code stays exact	63 → 20 tokens, same fix
Read less	Logs, JSON, CSV, test output shrink before the model reads them	33.2% fewer input tokens per session
Auto · new	Picks the model and the effort for each ask	54% cheaper than Opus at xhigh, same score
Blocks · new	Code mode: agent keeps the scripts it writes and runs them again	397 → 76 tokens for one test run
Waste fixes	Finds where your tokens go and fixes it. New: keeps the prompt cache warm while you pause	Not measured yet
Browse	Web pages come back compressed	129.8× smaller page

caveman status shows what is on. caveman off browse turns one off. Only Auto needs an account, and it is free. 4.0.0 release notes

Proof

Outside labs first. Ours come with each rock below. Nothing rounded up. Red rows stay red.

Who	Setup	Result
Adobe Research, CAVEWOMAN paper (cites this repo)	Caveman-style output, eight models, five datasets	Cost cut 1.4 to 2.4× per model, up to 3×
Elastic, Elasticsearch Labs	Caveman mode remade for Elasticsearch, eight live MCP scenarios	63.6% fewer response tokens. "Zero information loss."
JetBrains	86 real coding tasks, paired A/B	No measurable quality loss (p = 0.82). 8.5% fewer output tokens

Two findings shaped caveman. Adobe: cavemanning your prompt makes answers worse, so caveman never touches your prompt. JetBrains: agent sessions are mostly code and tool calls, which the voice leaves alone. So caveman grew rocks that shrink what the agent reads and what it runs on.

Say less: the caveman voice

A voice, not broken grammar. Every reply follows the same structure.

Rule	What it means
Answer first	[thing] [action] [reason]. [next step]. No greeting, no "let me", no recap
One idea per sentence	Built on ASD-STE100, the controlled English of aircraft maintenance manuals: 20 words max, active voice, one term per thing
Meaning never dropped	Articles can go. not, never, no, only never go. Numbers and units stay exact
Payload verbatim	Code, commands, paths, and error messages untouched, character for character
No theater	No "me think". No chatter between tool calls. If caveman phrasing isn't shorter, plain wins
Knows when to stop	Security warnings, irreversible actions, and confused users get full sentences. Then grunt resumes
Your prompts stay yours	Never rewritten. Research say that backfire

Ten dev questions on claude-opus-5-5:

Instruction	Output tokens
None	6,983
Answer concisely.	4,334
/caveman	4,119
/ultracave	2,693

"Be concise" is the real baseline; new models already know it. On top of it, /caveman cuts 3% more at the median and /ultracave 35% more. Measured on the 3.1.0 rules, not yet re-run. The rules cost about 1,160 tokens of input, and if you pay per request (GitHub Copilot), shorter answers save nothing. Harness · Every case where caveman loses