wehub-resource-sync
1.6 KiB
1.6 KiB
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 (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
# 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).