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11pyo/AINavManifest

AI Manifest

License: MIT Patent: FRAND IETF Draft Korean Patent Tokens Success

Embedded workflow instructions for AI agents — enabling efficient web UI automation without repeated DOM analysis.

Korean Patent Application No. 10-2026-0071716 (filed 2026-04-21) · IETF Internet-Draft draft-han-ai-manifest-00 · MIT License · FRAND terms for patent claims


Why

LLM-based AI agents (Claude Code, MCP clients, Puppeteer/Playwright-driven tools) currently parse entire DOMs or screenshots on every page, wasting tokens and failing on complex multi-step transactions. Website operators have no standardized way to declare "AI-Ready" workflows.

AI Manifest is a JSON specification that websites embed to tell AI agents exactly how to operate their UIs — step by step, with CSS selectors and actions.

Without manifest:  AI analyzes full DOM/screenshots repeatedly → high token cost, frequent failures
With manifest:     AI reads instructions → executes directly via CSS selectors → done

Empirical Results

Benchmark: ERP-style 2-step order entry transaction, n=30 iterations, tiktoken(cl100k_base).

Metric Baseline (DOM analysis) AI Manifest Improvement
Mean input tokens 1887.6 341.0 −81.9%
Task success rate 20.0% (6/30) 100.0% (30/30) +80.0 %p
Mean LLM calls 1.4 1.0 −0.4

Reproducible benchmark code lives in validation/.


Protocol Overview

Three embedding methods (sites can combine):

Method A — Well-Known URI

<meta name="ai-manifest" content="/.well-known/ai-manifest.json">

Serve the JSON at /.well-known/ai-manifest.json per IETF RFC 8615.

Method B — Hidden DOM Element

<div id="ai-manifest" style="display:none" aria-hidden="true"
     data-manifest='{"version":"1.0", ...}'></div>

Method C — HTTP Response Header

X-AI-Manifest: url=/.well-known/ai-manifest.json; hash=sha256:...

Agents fetch the manifest, compute its SHA-256 hash over a canonical (key-sorted, UTF-8) byte sequence, and verify against a central trust registry before executing steps[] sequentially.


Trust & Security

A Central Trust Registry prevents malicious sites from injecting harmful instructions into AI agents (prompt injection defense):

AI Agent → detects manifest → queries registry.aimanifest.io/verify
                                      ↓
                          Trusted  ✅ → Execute steps
                          Unknown  ⚠️ → Warn user, fall back to DOM analysis
                          Blacklist ❌ → Refuse and alert user

The registry also performs static analysis of submitted manifests — detecting suspicious selector patterns (iframe injection, external form submissions), disallowed actions, and untrusted value sources — automatically blacklisting risky manifests.


Schema

See ai-manifest.schema.json for the full JSON Schema (Draft-07).

Supported Actions

Action Description
click Click a button or link
fill Type text into an input field
select Choose an option from a dropdown
upload Upload a file to a file input
wait Wait for a condition or timeout
scroll Scroll to an element
navigate Go to a URL
assert Verify a condition before proceeding
hover Hover over an element

Examples

Example File
Academic manuscript submission (ScholarOne-like) examples/academic-submission.json
SAP Material Master creation (MM01) examples/sap-material-create.json

How This Differs from Related Standards

Standard Purpose Covers step-by-step UI?
robots.txt Crawling permissions
llms.txt LLM-friendly documentation
agents.txt / agent-permissions.json Agent capability & permission declarations
OpenAI ai-plugin.json API integration manifest
ai-manifest Step-by-step UI workflow instructions with trust verification

Patent Notice

This protocol is subject to:

Korean Patent Application No. 10-2026-0071716 · Filed 2026-04-21 · Applicant: Won-pyo Han

  • Code in this repository (including the JSON Schema, validation harness, and examples) is licensed under the MIT License.
  • Patent claims are offered under FRAND (Fair, Reasonable, and Non-Discriminatory) terms to promote adoption as an open standard. See docs/FRAND.md for the full declaration.
  • Early publication of the Korean application has been requested (public publication expected within ~2–3 months of filing).

International counterparts (PCT, direct national filings) may be pursued within 12 months of the Korean priority date (until 2027-04-21).


Roadmap

  • v0.1 schema and reference implementation
  • IETF Internet-Draft: draft-han-ai-manifest-00 — posted 2026-04-21
  • SDK: auto-generate manifests from existing web UIs (Python, Node.js)
  • Central Trust Registry deployment: registry.aimanifest.io
  • AI-Certified badge program for compliant websites
  • Collaboration with W3C / IETF standardization tracks

Contributing

Issues, schema proposals, and implementation PRs welcome. Please read docs/FRAND.md before contributing patentable improvements.


License


Author

Won-pyo Han · pk102h@naver.com

About

Embedded workflow instructions for AI agents. Korean Patent 10-2026-0071716. MIT + FRAND for open standardization.

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