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 niels-emmer/myace --skill eu-ai-act-transparencygit clone --depth 1 https://github.com/niels-emmer/myaceWrote 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/niels-emmer/myace/eu-ai-act-transparency)<a href="https://agentmods.dev/skills/niels-emmer/myace/eu-ai-act-transparency"><img src="https://agentmods.dev/badge/skills/niels-emmer/myace/eu-ai-act-transparency/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/niels-emmer/myace/eu-ai-act-transparency"><img src="https://agentmods.dev/badge/skills/niels-emmer/myace/eu-ai-act-transparency.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00045 | $0.00997 |
| Opus 5 | $0.00023 | $0.00498 |
| Sonnet 5 | $0.00009 | $0.00199 |
| Haiku 4.5 | $0.00005 | $0.00100 |
Grade A, and why
EU AI Act Transparency 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Give reviewers a concrete checklist for the Article 50 transparency obligations under Regulation (EU) 2024/1689. These apply to limited-risk systems too — not just high-risk ones — and are enforceable from 2 Aug 2026. This is the skill the eu-ai-act-compliance-reviewer agent applies to transparency.
When to use it
Whenever a system interacts with people (chatbot/virtual assistant), generates or manipulates synthetic content (image, audio, video, text), recognises emotion, or categorises people biometrically. Also when reviewing a deployer's handling of AI-generated content.
The four obligations
Art 50(1) — AI interaction disclosure (chatbots and virtual assistants)
Providers must ensure that systems intended to interact directly with natural persons are designed so the person is informed that they are interacting with an AI system, unless this is obvious from the circumstances. Applies at the time of first interaction, in a manner that meets accessibility requirements. A site-wide footer disclaimer is not sufficient — the disclosure must be at the point of interaction.
Art 50(2) — Machine-readable marking of synthetic content
Providers of generative AI systems (including GPAI) must ensure outputs are marked in a machine-readable format and detectable as artificially generated or manipulated. This covers all modalities — audio, image, video, text. Implement via C2PA content credentials, invisible watermarking, or provenance metadata in API responses. The marking must survive the distribution pipeline. (Generative systems placed on the market before 2 Aug 2026 have until 2 Dec 2026 to meet this duty.)
Art 50(3) — Emotion recognition / biometric categorisation notice
Deployers of emotion-recognition or biometric-categorisation systems must inform the natural persons exposed to them. First screen the use case against the Art 5 prohibition (emotion recognition in workplaces/education is banned); for permitted uses, design a clear, distinguishable notice mechanism.
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.
- 11d ago First seen · 52 lines · 45 tokens per session scan A abb67b54a3c4
EU AI Act Transparency is a skill published in the GitHub repository niels-emmer/myace (1 stars, last pushed 5d ago), licensed MIT. It adds 45 tokens to every session and 997 once invoked, about $0.0002 per session on Opus 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 2026-08-31.
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