Squeeze your prompts
down to their essence.

A local, four-stage compressor for LLM content — it keeps the salient sentences, trims the rest, and fits a token budget. No inference, no network calls.

圧縮 · Compress
Awaiting input.
A note on short inputs Compression is extractive and tuned for long, repetitive content — logs, code, and verbose prose. On very short inputs the model-specific framing added in the Adapt stage can outweigh the savings, so the compression figure may be zero or negative. This is expected; the ratio turns positive as input length grows.
仕組み · How it works

Four pure stages, run in order. Each is deterministic — the same input always yields the same output.

01

抽出 Extract

Keeps the sentences with the highest keyword salience.

02

統合 Synthesise

Dedupes, shortens stock phrases, abbreviates.

03

優先 Prioritise

Enforces the token budget, keeping head and tail.

04

適応 Adapt

Adds model-specific framing for Claude, GPT or Cursor.

接続 · API

The same engine is available over HTTP. Post your content to /api/optimise and receive the compressed text plus metrics. The command on the right reflects your current settings.

EndpointPurpose
POST /api/optimiseCompress one document
POST /api/batchUp to 50 at once
POST /api/optimise-for-aiBalanced, per model
GET /api/statsCapabilities
GET /healthLiveness
Example request