Print gave us PDF. Photography gave us JPEG. Music gave us MP3.
The AI era generates more content than any previous era — but has no format to carry
trust, provenance, or verification with that content.
Today I'm releasing AKF — Agent Knowledge Format. Open source. Open spec.
What is it?
AKF is EXIF for AI. ~15 tokens of JSON that embed directly into any file:
- Trust scores — how reliable is this content? (0-1)
- Source provenance — where did it come from? (SEC filing → analyst → AI summary)
- Security classification — who can see it? (public, internal, confidential)
- AI attribution — which model generated it?
- Compliance metadata — does it meet EU AI Act, SOX, NIST requirements?
Install
pip install akf # Python
npm install akf-format # TypeScript
30-Second Demo
# Stamp a file
akf stamp report.md --agent claude --evidence "generated from quarterly data"
# See what's inside
akf inspect report.md
# Check compliance
akf audit report.md --regulation eu_ai_act
# Embed into Word
akf embed report.docx
Zero Touch
eval "$(akf shell-hook)"
# Now every file Claude, ChatGPT, OpenClaw, Aider, Ollama creates is auto-stamped
Why Now
The EU AI Act Article 50 takes effect August 2, 2026. AI-generated content
published for public interest must carry transparency metadata. Penalties: up to
€35M or 7% of global turnover.
Colorado's SB 205 follows on June 30, 2026. DORA is already enforced.
AKF maps directly to these requirements. One command gives you a compliance report.
Integrations
Ships with integrations for LangChain, LlamaIndex, CrewAI, MCP (Model Context
Protocol), VS Code, and GitHub Actions.
Links
- Website: akf.dev
- GitHub: HMAKT99/AKF
- Spec: akf-v1.1.schema.json
Open source. MIT licensed. Feedback welcome.
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