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Akf trust metadata

Skill newmindsgroup/ai-agent-skills-library/sources/sickn33-antigravity-awesome-skills/skills/akf-trust-metadata

Shared library of AI agent skills — works across Claude Code, Cursor, Codex, Windsurf, OpenCode, and Google Antigravity via a single universal installer.

Install
npx -y skills add newmindsgroup/ai-agent-skills-library --skill akf-trust-metadata

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What its author says it does

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The AI native file format. EXIF for AI — stamps every file with trust scores, source provenance, and compliance metadata. Embeds into 20+ formats (DOCX, PDF, images, code). EU AI Act, SOX, HIPAA auditing.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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AKF — The AI Native File Format

Every photo has EXIF. Every song has ID3. AKF is the native metadata format for AI-generated content.

When to Use

Use this skill when you need to stamp, inspect, or audit provenance and trust metadata on AI-generated or AI-modified files for compliance, review, or handoff workflows.

After creating or modifying files

akf stamp <file> --agent <agent-name> --evidence "<what you did>"

Evidence examples:

  • "generated from user prompt"
  • "refactored existing code"
  • "tests pass"
  • "docs reviewed"

Before modifying existing files

akf read <file>          # Check existing trust metadata
akf inspect <file>       # See detailed trust scores

Compliance auditing

akf audit <file> --regulation eu_ai_act    # EU AI Act Article 50
akf audit <file> --regulation hipaa         # HIPAA
akf audit <file> --regulation sox           # SOX
akf audit <file> --regulation nist_ai       # NIST AI RMF

Classification

  • --label confidential for finance/secret/internal paths
  • --label public for README, docs, examples
  • Default: internal

Install

pip install akf

Links

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Keep looking

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