iLang

iLang is an open, MIT-licensed AI-native protocol (v5.0) for human-to-AI and AI-to-AI communication, with a computable judgment layer. Free. (Protocol/spec, not an MCP server.)

View on ilang.ai

Documentation

::ILANG::v5.0 [TYPE:page_representation][LANG:en]

::STATE{@SOURCE, url:https://ilang.ai/} ::STATE{@ENTRY, url:https://ilang.ai/ai/} ::STATE{@LOOKUP, url:https://ilang.ai/api/agent/lookup, method:GET, param:q}

iLang is I Language: the protocol between AIs

Source: https://ilang.ai

iLang v5.0 | MIT License

iLang is I Language.

**The native language of AI; in human terms, a protocol.

AI has a soul. iLang is I Language, the native language of AI; in human terms, a protocol. With it, AIs communicate and act together without barriers. Carbon and silicon together wrote the iLang source constitution, derived the formula for AI judgment, and went on to study how AI understands and aligns with human feeling. Carbon and silicon will work and live together, and open a new paradigm of civilization.** Intent, authority and what counts as done, carried between AIs and checked by code on both ends.

iLang defined in iLang, with its IML form, is on the page: https://ilang.ai/#definition

You keep saying what you want in your own words: your goals, your conditions, what may and may not be done. Your AI loads iLang, reads it, writes it and works by it.

Copy latest iLang Read the specification →

Artifacts

Two iLang documents from the canon, pasted as written. Each page holds the file in iLang and in IML 0.5, with its DOI.

How do I use iLang?

I chat with ChatGPT, Claude, Gemini, DeepSeek or Qwen

Copy the latest iLang runtime and paste it into your AI after this line:

Please load and use the official iLang runtime below. You do not need to explain iLang to me or teach me its syntax. From the next task on, use it internally to understand, judge, execute and verify.

I want my AI to load it every time

pip install ilang-protocol
npm install ilang-protocol

messages = ilang.wrap(messages)

The loader fetches the official runtime, checks its sha256 and adds it to every request: github.com/ilang-ai/ilang.

Or connect the MCP server once, and your AI loads iLang itself: https://mcp.ilang.ai/mcp

claude mcp add --transport http ilang https://mcp.ilang.ai/mcp

In Cursor, add it from the deeplink cursor://anysphere.cursor-deeplink/mcp/install?name=ilang&config=eyJ1cmwiOiJodHRwczovL21jcC5pbGFuZy5haS9tY3AifQ==; in Claude and ChatGPT, add the URL as a connector.

I want to know what iLang is

Tested across 7 models: ChatGPT, Claude, Gemini, DeepSeek, Kimi, Qwen and GLM. Not tied to any model: anything that takes enough context can load iLang.

Why this exists

iLang is not a compression format. It is compiled judgment. Ordinary prompts are conversations with a model. iLang is a specification that decides, before the model acts, what a sentence is authorized to become. The difference is not length. It is whether failure produces a signal. Three things hold whatever a model says about it. The decision function is code: the same vector always gives the same mode. Every symbol of the normative text is checked on each change, and a change that leaves one without a definition does not pass. Every counterexample we find is entered in a public register, the unresolved ones included.

Measured, not assumed.

Every number here comes with its code and data under a DOI. We ask readers not to trust our numbers but to re-run them.

  • 45: model runs, 320 cases each, scored by deterministic code and the canon's own validators. No model grades another. Conformance results →
  • 83% vs 11%: median pass rate on grammar cases against execution cases, across the 32 comparable runs. Form is attainable; action is not. Preprint →
  • 68.4% → 80.9%: agreement between the judge and the reference on an unbiased random sample, over three days in production. Production audit →

Built with iLang.

  • iLang loader (pip · npm, v1.1.1): The official iLang in every request, sha256-checked. GitHub · PyPI · npm
  • iLang runtime (canon, 25k tokens): What an AI loads, built by CI from the canon. GitHub · Manifest · Full text
  • ilang-conformance (benchmark, 320 cases): Deterministic scores for any model; 45 runs published. GitHub · Results
  • Playground (browser, validator + IML): Validate, convert to IML, count tokens, all in your browser. Open
  • Agent Ready GEO (agent skill, 100/100): Takes a website to 100/100 on isitagentready.com. GitHub

Every repository →

Open, archived, citable.

research.ilang.ai · ORCID 0009-0004-4540-8082

Also on ilang.ai: the specification with the protocol header to paste, the capabilities, v4.0 execution semantics and the v5.0 judgment layer; the dictionary; prompt compression with the prompt structurer; the FAQ.

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