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 seb1n/awesome-ai-agent-skills --skill eu-ai-act-readinessgit clone --depth 1 https://github.com/seb1n/awesome-ai-agent-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/seb1n/awesome-ai-agent-skills/eu-ai-act-readiness)<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/eu-ai-act-readiness"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/eu-ai-act-readiness/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/seb1n/awesome-ai-agent-skills/eu-ai-act-readiness"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/eu-ai-act-readiness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00136 | $0.02502 |
| Opus 5 | $0.00068 | $0.01251 |
| Sonnet 5 | $0.00027 | $0.00500 |
| Haiku 4.5 | $0.00014 | $0.00250 |
Grade A, and why
eu-ai-act-readiness 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 9d 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
EU AI Act Readiness
Produce operational triage, not a legal opinion. The AI Act changes through amendments, delegated/implementing acts, guidance, standards, and national enforcement practice; verify the law and dates at the start of every assessment.
Inputs
Collect or state:
- Assessment date, target EU/EEA countries, organization locations, customer/user locations, and where system outputs are used.
- Each AI system/model's purpose, intended use, use-case screen, reasonably foreseeable misuse, lifecycle status, exact system/model versions, launch/change dates, material modifications, and affected people.
- Organization role(s) for each system: provider, deployer, importer, distributor, product manufacturer, authorised representative, or GPAI model provider.
- Model/vendor chain, branding, fine-tuning or substantial modifications, integrations, data sources, and contract allocation.
- Jurisdictions, decision domain, degree of automation, human-oversight design/authority, outputs, transparency interface, monitoring, incidents, complaint/appeal paths, and explicit reassessment triggers.
- Existing risk, quality, privacy, security, accessibility, procurement, recordkeeping, and AI-literacy evidence.
Use the blank AI system inventory template when no reliable inventory exists.
Output contract
Return:
- Assessment date, last-verified legal-source date, jurisdictions, official sources, assumptions, and limitations.
- An inventory with jurisdiction, system/model version, preliminary EU nexus, operator role, use-case screen, foreseeable misuse, material modifications, automation/oversight, risk-status hypothesis, classification basis/confidence, and reassessment triggers.
- A gap register mapping provision/topic, applicable milestone, current evidence, gap, priority, owner, target date, and verification method.
- Separate sections for prohibited-practice escalation, Article 50 transparency, high-risk systems, GPAI models, and broadly applicable governance such as AI literacy.
- A 30/60/90-day implementation plan plus questions requiring qualified EU counsel or a competent authority.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 144 lines · 136 tokens per session scan A 1d19bcd1a7e3
eu-ai-act-readiness is a skill published in the GitHub repository seb1n/awesome-ai-agent-skills (179 stars, last pushed 1mo ago), licensed MIT. It adds 136 tokens to every session and 2,502 once invoked, about $0.0007 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 2026-09-03.
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