caveman
A Matt Pocock Claude Code skill that switches the assistant into an ultra-compressed communication mode — drops articles, filler, pleasantries, and hedging while keeping full technical accuracy. Persistent once active, with an auto-clarity exception that suspends compression for security warnings and irreversible-action confirmations.
Compress response style until told otherwise
Trigger phrases
Phrases that activate this skill when typed to Claude Code:
caveman modetalk like cavemanless tokensbe brief
What it does
caveman switches Claude into a compressed response style and stays there for the rest of the session until explicitly cancelled.
The rules:
- Drop: articles (a/an/the), filler (just/really/basically/actually/simply), pleasantries (sure/certainly/of course/happy to), hedging.
- Use: sentence fragments, short synonyms (big not extensive, fix not “implement a solution for”), abbreviations (DB/auth/config/req/res/fn/impl), arrows for causality (X → Y).
- Preserve verbatim: technical terms, code blocks, error quotes.
A pattern the skill names directly: [thing] [action] [reason]. [next step].
Worked example from the SKILL.md:
Not: “Sure! I’d be happy to help you with that. The issue you’re experiencing is likely caused by…”
Yes: “Bug in auth middleware. Token expiry check use
<not<=. Fix:”
Persistence is explicit in the skill: ACTIVE EVERY RESPONSE once triggered. No filler drift, no revert after many turns. Off only on “stop caveman” or “normal mode.”
Auto-clarity exception. The skill suspends compression temporarily for: security warnings, irreversible-action confirmations, multi-step sequences where fragment-order risks misread, and any time the user asks to clarify or repeats a question. Caveman resumes once the clarity-sensitive part is done.
When to use it
Reach for it when:
- Token economics matter for the session — long autonomous loops, cost-sensitive workflows, or context-window pressure
- The back-and-forth is dense enough that pleasantries add friction the operator notices
- You’ve configured the agent for code-heavy work where prose around the code is overhead
When not to reach for it:
- The session involves walking another operator through a process and friction is the point
- You’re producing artifacts (blog drafts, customer-facing copy) where the prose itself is the deliverable — compression is for chat, not artifact text
- Multi-step destructive sequences where the auto-clarity exception would be triggering on every turn anyway
Install
The skill is distributed via Pocock’s skills repo. Install via his recommended path (npx skills add or manual copy of the SKILL.md into .claude/skills/caveman/) — see the repo README for canonical install instructions.
Once installed, trigger with one of the activation phrases. The mode persists until you explicitly cancel.
What a session looks like
The first turn after activation is the calibration: the agent’s response gets visibly shorter, technical terms intact, articles and pleasantries gone. After that, every turn maintains the compression unless the auto-clarity exception fires.
The persistence rule is load-bearing — without it, the agent tends to drift back to its default conversational tone after a few turns. The “no revert after many turns” instruction is what keeps it pinned.
Receipts
TODO — to be filled in from a real session. Note on the upstream claim: the upstream description cites a token reduction figure; under this site’s attribution rules we don’t republish numerical claims without firsthand verification, so the number is omitted here. When the skill is triggered in production use, capture: actual token-per-response delta over a multi-turn session (measured, not estimated), how often the auto-clarity exception fired, and whether the model drifted back to default style at any point or stayed pinned across the full session.
Source and attribution
Originally written by Matt Pocock. The canonical SKILL.md lives in the productivity/caveman folder of his public skills repository.
License: MIT. You can install, adapt, and redistribute the skill, with attribution preserved.
This page documents the skill from a practitioner’s perspective. For the formal spec and any updates, defer to the source repo.