Distil

Something is rewriting your agent's context.
Distil measures what it cost you.

Your provider now edits the context window for you — clearing old tool results, summarizing history — by default, server-side, with no report of what changed.
Distil is the instrument that answers the only question that matters: did the agent still do the same thing?

Distil also compresses — the tool output, logs, and history your agent re-sends every turn, reversibly.
It's the one context operation that ships with its own certificate, its own adversarial gate, and a number it is willing to refuse to print.

The 60-second version

Compression that cannot be checked is a guess about your agent's behaviour.
Distil is built so every part of it is checkable, and so the checks are allowed to come back no.

• It proves decision-equivalence per request — and can say no. Shadow mode replays a sampled request three times: twice on the original context and once on the compressed one, then reports 1{A=B} − 1{A=A'} — a paired difference against the model's own self-agreement, with a bootstrap 95% CI, unclipped, so it is allowed to be negative. One reporting floor (50 A/B + 30 A/A) gates every surface; below it, every surface says below reporting floor instead of a number. The current live sample is below that floor, and the status line says so.
• What it folds, it can give back byte-exact. A digest is a marker plus a handle into a local content-addressed store, and the agent gets a distil_expand tool to recover the original mid-task. The gateway ships Tier-0 only rather than emit a stub it cannot restore.
• It will not digest a line your agent has to quote back. An Edit(old_string=…) is a literal match. Reading exact-quote provenance from the shell command, not just the tool name, took byte-exact quote loss from 39.3% → 16.2% on real coding traffic — and it costs real savings, which we price rather than hide.
• It does not break your prompt cache. Compression is suffix-only and cache-monotonic by construction: a later turn may never rewrite bytes the provider has already cached. We shipped that bug once, measured it at 2× the cost of compressing nothing, and made the invariant enforced. The cache contract →
• It has been pointed at a hostile input, not just a hard one. distil validate --adversarial runs a COMA-class battery through the same path the proxy uses, and we publish the two cases that do not come back clean. Threat model →
• Every rung of the dial is measured, not just the default. distil bench --curve traces savings against fact recall across the whole ladder, offline and free. The curve →

What it does

• Wrap your agent — 11 presets: distil wrap -- claude · codex · gemini · aider · opencode · qwen · goose · grok · openhands · copilot · kimi. Zero config, no code change.
• Run a proxy — point any base_url client at it. Python, TypeScript, any language, any framework. Sync proxy, async proxy, and a standalone gateway, with the same provider coverage in each: Anthropic Messages, OpenAI Chat Completions and the Responses API, Azure OpenAI, and Gemini generateContent.
• Call it as a library — from distil import compress_messages in your own agent loop.
• Give your agent a recall tool — MCP server: it compresses its own output and gets the exact bytes back on demand.
• Framework hooks — LangChain · LangGraph · LiteLLM · Agno · Strands · AutoGen · LlamaIndex, in-process, no network hop — plus an ASGI middleware for any Starlette/FastAPI app that hosts its own LLM endpoint, and the npm package for the Vercel AI SDK.
• On a subscription — distil hook --install: Claude Code compresses its own tool output through the documented PostToolUse extension point. No proxy, no credentials touched. distil quota shows the rate-limit window it buys back. Details →
• See what it did — live status line, session dissect, per-request headers, OTel spans, Prometheus metrics.

pipx install distil-llm && distil onboard    # detects your agent + billing, wires everything

Not sure which of those you want? Two questions pick your mode → — plain language, honest savings ranges, no jargon.

Will it save you money? On metered billing (an API key), yes — directly, off the bill. On a flat-rate Pro/Max subscription there is no per-token bill to cut, but there is a rate-limit window, and spending fewer tokens per turn leaves more of it for the next task. distil quota shows that window live. Savings come from large, repetitive tool output: verbose JSON and duplicated log runs compress 25–99%, while prose and unique-line output compress ~0% — a short session that never reads a big file showing near 0% is the tool working correctly, not failing. Why →

_{◉  LIVE · measured from the opt-in census on a public git branch, never estimated}

▶  Watch the counter tick live & audit every number →