AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sickn33/agentic-awesome-skills --skill akf-trust-metadatagit clone --depth 1 https://github.com/sickn33/agentic-awesome-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sickn33/agentic-awesome-skills/akf-trust-metadata)<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/akf-trust-metadata"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/akf-trust-metadata/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/akf-trust-metadata"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/akf-trust-metadata.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00060 | $0.00624 |
| Opus 5.5 | $0.00024 | $0.00250 |
| Sonnet 5.5 | $0.00012 | $0.00125 |
| Haiku 4.5 | $0.00006 | $0.00062 |
Grade A, and why
akf-trust-metadata scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
8 near-identical copies found in the catalogue:
- akf-trust-metadata — 100% identical, 10 lines differ
- akf-trust-metadata — 100% identical, 10 lines differ
- akf-trust-metadata — 100% identical, 10 lines differ
- akf-trust-metadata — 100% identical, 10 lines differ
- akf-trust-metadata — 100% identical, 10 lines differ
- akf-trust-metadata — 100% identical, 10 lines differ
- akf-trust-metadata — 100% identical, 10 lines differ
- akf-trust-metadata — 100% identical, 10 lines differ
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
Scope and Evidence
Use a reviewed, project-pinned installation; inspect the installed CLI help before using version-dependent flags. Stamping modifies files: confirm the target scope, preserve originals and verify metadata plus content integrity afterward. Trust scores and labels are declarations, not independent proof of accuracy or legal compliance. Never stamp “tests pass” unless the actual named checks passed for the exact artifact. Keep confidential data out of metadata that may travel with shared files.
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
Advisory Metadata Checks
The following upstream-style command examples inspect metadata fields. Their output cannot certify regulatory compliance; verify applicability and requirements separately.
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 confidentialfor finance/secret/internal paths--label publicfor README, docs, examples- Default:
internal
Install
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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago Changed · +6 lines af8b43385127
- 1mo ago First seen · 74 lines · 60 tokens per session scan A 8ed26e4794e4
akf-trust-metadata is a skill published in the GitHub repository sickn33/agentic-awesome-skills (48,548 stars, last pushed 2d ago), licensed MIT. It adds 60 tokens to every session and 624 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
Other skills, from other repositories
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.
akf-trust-metadata-v2
AKF — The AI Native File Format workflow skill. Use this skill when the user needs 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 and the operator should preserve…
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.
akf-trust-metadata
AKF — The AI Native File Format workflow skill. Use this skill when the user needs 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 and the operator should preserve…
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.
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.