Token compression
Token compression
Coding-agent skills that cut LLM token usage — and cost — without losing correctness.
Token compression tools make AI coding agents emit less — less code, less prose — while keeping correctness intact. Fewer generated tokens means lower API cost, faster responses, and lower energy use per request, in line with GreenPT's sustainability goals.
Three open-source skills, from most to least comprehensive:
| Tool | Focus | Headline |
|---|---|---|
| Honey | Less code and less prose, plus dense agent-to-agent handoffs | ~49% fewer code tokens at 98% of baseline quality |
| Ponytail | Minimal code (YAGNI) | ~54% less code (up to 94%), ~20% cheaper, ~27% faster |
| Caveman | Terse prose | ~75% fewer output tokens, full technical accuracy |
Honey combines what Ponytail (minimal code) and Caveman (terse prose) do separately, then adds auto-intensity, safety carve-outs, and compressed subagent handoffs.