akf-trust-metadata
AKF is a metadata embedding system that stamps AI-generated files with trust scores, source provenance, and compliance information across 20+ formats including DOCX, PDF, images, and code. Use this skill when auditing file lineage for regulatory compliance (EU AI Act, HIPAA, SOX), documenting AI modifications, or establishing chain-of-custody for sensitive AI-generated content in review and handoff workflows.
git clone --depth 1 https://github.com/sickn33/antigravity-awesome-skills /tmp/akf-trust-metadata && cp -r /tmp/akf-trust-metadata/plugins/antigravity-awesome-skills-claude/skills/akf-trust-metadata ~/.claude/skills/akf-trust-metadataSKILL.md
# 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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