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Caveman Micro

Development community

Description

6-line caveman micro prompt (85 tokens) that outperformed the original 552-token skill. Benchmark on Claude Sonnet + Opus included.

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

caveman-micro

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**6 lines. 85 tokens. Outperformed the 552-token original.**

We benchmarked the viral [caveman](https://github.com/JuliusBrussee/caveman) token-saving prompt on real coding tasks. Then we distilled it into 6 lines that beat the original on both Claude Sonnet and Opus.

The micro prompt

Respond like smart caveman. Cut all filler, keep technical substance.
- Drop articles (a, an, the), filler (just, really, basically, actually).
- Drop pleasantries (sure, certainly, happy to).
- No hedging. Fragments fine. Short synonyms.
- Technical terms stay exact. Code blocks unchanged.
- Pattern: [thing] [action] [reason]. [next step].

Copy it into your system prompt, custom instructions (ChatGPT), or CLAUDE.md. Works with any LLM.

Benchmark results

Tested on real tasks (incident diagnosis, config extraction) with structured JSON output and quality verification.

Claude Sonnet

Group Avg Output Tokens Quality Savings
Baseline ("Be concise") 259 100% --
Caveman full (552 tok) 225 100% 13%
Caveman Micro (85 tok) 223 100% 14%

Claude Opus

Group Avg Output Tokens Quality Savings
Baseline ("Be concise") 227 100% --
Caveman full (552 tok) 207 100% 9%
Caveman Micro (85 tok) 180 100% 21%

Quality: 100% in every run. Zero missing facts. The micro version outperformed the full skill on both models.

Why micro beats full

The model already knows how to be concise. It doesn't need a 552-token tutorial. It needs 6 lines of permission.

A longer instruction set costs tokens to inject and gives the model more noise to process. The short nudge does the same job at one-sixt