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-gpaigit 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-gpai)<a href="https://agentmods.dev/skills/niels-emmer/myace/eu-ai-act-gpai"><img src="https://agentmods.dev/badge/skills/niels-emmer/myace/eu-ai-act-gpai/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-gpai"><img src="https://agentmods.dev/badge/skills/niels-emmer/myace/eu-ai-act-gpai.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 | $0.00053 | $0.00931 |
| Opus 5 | $0.00026 | $0.00465 |
| Sonnet 5 | $0.00011 | $0.00186 |
| Haiku 4.5 | $0.00005 | $0.00093 |
Grade A, and why
EU AI Act General-Purpose AI 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.
How it starts
The opening of the file, as written. The whole thing — 56 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 obligations on providers of general-purpose AI (GPAI) models under Regulation (EU) 2024/1689, Articles 51-55. GPAI obligations entered into application on 2 Aug 2025. This is the skill the eu-ai-act-compliance-reviewer agent applies to GPAI.
When to use it
Whenever the org is a provider of a GPAI model (a foundation model / large language model placed on the market), or a downstream provider building an AI system on a GPAI model and needing to understand what flows down from the upstream provider.
The obligations
Art 51 — Classification of GPAI models with systemic risk
A GPAI model is presumed to have systemic risk if it has high-impact capabilities (cumulative training compute above a threshold, ~10^25 FLOPs). The provider must notify the AI Office if the model meets the threshold or is designated as having systemic risk.
Art 53 — Obligations for all GPAI model providers
- Technical documentation — draw up and keep up to date, including training approach, data sources, capabilities and limitations, and evaluation results, sufficient for the AI Office and downstream providers to understand the model.
- Copyright policy — put in place a policy to comply with Union copyright law, in particular to identify and respect reservations of rights (opt-outs) expressed under the DSM Directive.
- Training-data summary — make publicly available a sufficiently detailed summary of the content used for training, per the Commission template.
Art 54 — Authorised representatives
Non-EU GPAI providers must appoint an authorised representative established in the Union before placing the model on the market.
Art 55 — Obligations for GPAI models with systemic risk
In addition to Art 53:
- Model evaluation — perform and document model evaluations, including adversarial testing, to identify and mitigate systemic risks.
- Risk assessment and mitigation — assess and mitigate systemic risks at Union level, including through model alignment, and report serious incidents to the AI Office.
- Cybersecurity — ensure an adequate level of cybersecurity protection for the model and its physical infrastructure.
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 First seen · 56 lines · 53 tokens per session scan A 494d27731932
EU AI Act General-Purpose AI is a skill published in the GitHub repository niels-emmer/myace (1 stars, last pushed 5d ago), licensed MIT. It adds 53 tokens to every session and 931 once invoked, about $0.0003 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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compliance
Use when scoping which regulatory frameworks bind a business — SOC 2, ISO 27001, HIPAA, PCI DSS, EU AI Act, DORA, NIS2 — building a control register with owners and evidence, or standing up the cadence that keeps it audit-ready. NOT drafting privacy-policy/ROPA/DPA or ToS text (that is gdpr-privacy, terms-conditions)…