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 lexbeam-software/eu-ai-governance-plugin --skill ai-act-compliancegit clone --depth 1 https://github.com/lexbeam-software/eu-ai-governance-pluginWrote 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/lexbeam-software/eu-ai-governance-plugin/ai-act-compliance)<a href="https://agentmods.dev/skills/lexbeam-software/eu-ai-governance-plugin/ai-act-compliance"><img src="https://agentmods.dev/badge/skills/lexbeam-software/eu-ai-governance-plugin/ai-act-compliance/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/lexbeam-software/eu-ai-governance-plugin/ai-act-compliance"><img src="https://agentmods.dev/badge/skills/lexbeam-software/eu-ai-governance-plugin/ai-act-compliance.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 | $0.00055 | $0.00759 |
| Opus 5 | $0.00028 | $0.00380 |
| Sonnet 5 | $0.00011 | $0.00152 |
| Haiku 4.5 | $0.00006 | $0.00076 |
Grade A, and why
ai-act-compliance 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 — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build an EU AI Act compliance programme
Follow LEGAL-SOURCE-PROTOCOL.md and read AI-ACT-DECISION-MAP.md. Retrieve deadlines and role-specific obligations from the Lexbeam EU AI Act MCP when available.
Establish the perimeter
Identify entities, jurisdictions, sectors, AI systems and GPAI models, roles, intended purposes, affected persons, product-law links, and existing governance. Do not turn a questionnaire into an assertion. Mark missing evidence.
Assess by control domain
Score each control effective, partly effective, absent, or not established, with an owner and evidence link:
- Inventory and role map: unique system record, purpose, owner, provider/deployer status, model dependencies, geography, data, and classification.
- Prohibited-practice control: complete Article 5 screening, approval gate, monitoring, and escalation.
- AI literacy: proportionate measures for providers’ and deployers’ staff and other operators under Article 4; do not invent a prescribed curriculum or guarantee.
- Classification and change control: Article 6 analysis, Article 6(3) evidence where used, Article 25 role-change triggers, and periodic reclassification.
- High-risk provider controls: Articles 9 to 17, 18 to 21, conformity assessment, declaration, CE marking, registration, post-market monitoring, and incident reporting, where applicable.
- High-risk deployer controls: Article 26 instructions, oversight, input-data relevance, monitoring, logs, workplace notice, affected-person notice, cooperation, DPIA linkage, and FRIA only where Article 27 applies.
- GPAI controls: distinguish Article 53 baseline duties from Article 55 systemic-risk duties and record the model-provider evidence relied upon.
- Transparency: assess each Article 50 obligation and transition separately.
- Evidence and assurance: approvals, versioning, change logs, testing, complaints, incidents, supplier evidence, and retention rules.
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 · 53 lines · 55 tokens per session scan A 97dbb6e9a085
ai-act-compliance is a skill published in the GitHub repository lexbeam-software/eu-ai-governance-plugin (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 55 tokens to every session and 759 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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