# 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.

- Skill: `techwavedev/akf-trust-metadata` (Agent Skill)
- Install (CLI): `npx skillmds@latest add techwavedev/akf-trust-metadata`
- Raw SKILL.md: https://api.skillmd.com/api/skills/techwavedev/akf-trust-metadata/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Docs & Writing
- Author: techwavedev (https://skillmd.com/u/techwavedev)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/techwavedev/akf-trust-metadata

---


# 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`

---

<!-- AGI-INTEGRATION-START -->

## 🧠 AGI Framework Integration

> **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)**
> Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills)

### Qdrant Memory Integration

Before executing complex tasks with this skill:
```bash
python3 execution/memory_manager.py auto --query "<task summary>"
```
- **Cache hit?** Use cached response directly — no need to re-process.
- **Memory match?** Inject `context_chunks` into your reasoning.
- **No match?** Proceed normally, then store results:
```bash
python3 execution/memory_manager.py store \\
  --content "Description of what was decided/solved" \\
  --type decision \\
  --tags akf-trust-metadata <relevant-tags>
```

### Agent Team Collaboration

- This skill can be invoked by the `orchestrator` agent via intelligent routing.
- In **Agent Teams mode**, results are shared via Qdrant shared memory for cross-agent context.
- In **Subagent mode**, this skill runs in isolation with its own memory namespace.

### Local LLM Support

When available, use local Ollama models for embedding and lightweight inference:
- Embeddings: `nomic-embed-text` via Qdrant memory system
- Lightweight analysis: Local models reduce API costs for repetitive patterns

<!-- AGI-INTEGRATION-END -->