caveman · alirezarezvani — Claude Code plugin: terse replies, fewer tokens
A compressed communication mode for Claude. The agent drops filler and pleasantries, keeps the technical content intact.
/plugin marketplace add alirezarezvani/claude-skills
/plugin install caveman@claude-code-skillsWhat caveman does
caveman switches Claude into a terse style. Instead of opening with a polite sentence, the agent goes straight to the answer, and the technical details stay accurate. Useful when verbose replies eat your token budget or you just want to read less.
The plugin ships three Python scripts built on the standard library. skills/caveman/scripts/caveman_compressor.py rewrites text by the mode's rules, token_savings_estimator.py measures how many tokens you save, and caveman_lint.py checks a reply against the style. Run any of them without arguments and it works on a built-in sample. There is also a cs-caveman-mode subagent and a /cs-caveman slash command for turning the mode on in one line. Python matters only for the scripts; the mode itself runs without it.
The base is Matt Pocock's caveman skill under MIT, and his wording plus the persistence rules carry over unchanged. The author layered tooling, three reference docs and a persona agent on top. Watch out for precise wording: legal or medical answers, or anything that leans on careful hedging, can lose meaning under compression, so switch the mode off there.
What it helps with
- cut token spend on long agent replies
- strip filler and pleasantries from answers
- check a finished reply against the terse style
- measure token savings on a chunk of text
- turn the compressed mode on for a whole session
Example prompts for the agent
- turn on caveman mode and keep answers short
- compress this text with
caveman_compressor.py - lint my reply with
caveman_lint.py
How to install caveman
Plugin marketplace
/plugin marketplace add alirezarezvani/claude-skills/plugin install caveman@claude-code-skillsStep by step, with commands for each platform: Claude Code plugins: marketplaces, installing, and building your own
Questions about caveman
How do I install caveman in Claude Code?
Add the marketplace with /plugin marketplace add alirezarezvani/claude-skills, then install the plugin: /plugin install caveman@claude-code-skills.
What does caveman do?
It puts the agent into a compressed style: no filler, articles or pleasantries, with technical accuracy kept. It also provides scripts for compressing text, estimating token savings and linting the style.
How is this different from Matt Pocock's original?
The voice and persistence rules come from his MIT-licensed caveman skill and stay verbatim. On top of that you get three Python scripts, reference docs, a cs-caveman-mode subagent and the /cs-caveman slash command.
Source text
caveman · MIT
# caveman Ultra-compressed communication mode. Cuts token usage ~75% by dropping filler, articles, and pleasantries while keeping full technical accuracy. ## Attribution **Derived from [Matt Pocock's caveman](https://github.com/mattpocock/skills/tree/main/skills/productivity/caveman)** (MIT). Matt's SKILL.md voice + activation triggers + persistence rules preserved verbatim per his MIT license. ## What this adds on top of Matt's original | Addition | Where | Why | |---|---|---| | **3 stdlib Python tools** | `skills/caveman/scripts/` | Compressor (apply Matt's rules deterministically), token-savings estimator (measure %), lint (verify response follows rules) | | **3 in-depth references** (5+ sources each) | `skills/caveman/references/` | Compression principles · Technical communication patterns · When caveman backfires (the auto-clarity exceptions, deepened) | | **cs-caveman-mode persona agent** | `agents/cs-caveman-mode.md` | Persistent caveman-mode operator with hard rules for technical-content exceptions | | **`/cs-caveman` slash command** | `commands/cs-caveman.md` | One-line trigger + persistence enforcer | ## Quick start ```bash # Compress text per Matt's rules python skills/caveman/scripts/caveman_compressor.py "Sure! I'd be happy to help you with that. The issue is..." # Estimate token savings on a piece of text python skills/caveman/scripts/token_savings_estimator.py "input text" # Lint a response to check caveman compliance python skills/caveman/scripts/caveman_lint.py "response text" ``` All three tools run with embedded samples if no input provided. ## License MIT (matching Matt's upstream).
© Alireza Rezvani · MIT · alirezarezvani/claude-skills
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