akf-trust-metadata
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.
Best use case
akf-trust-metadata is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using akf-trust-metadata should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/akf-trust-metadata/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How akf-trust-metadata Compares
| Feature / Agent | akf-trust-metadata | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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 ```bash 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 ```bash akf read <file> # Check existing trust metadata akf inspect <file> # See detailed trust scores ``` ## Compliance auditing ```bash 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 ```bash pip install akf ``` ## Links - https://akf.dev - https://github.com/HMAKT99/AKF - npm: `npm install akf-format` ## 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.
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