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 d-o-hub/github-template-ai-agents --skill eu-ai-act-compliancegit clone --depth 1 https://github.com/d-o-hub/github-template-ai-agentsWrote 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/d-o-hub/github-template-ai-agents/eu-ai-act-compliance)<a href="https://agentmods.dev/skills/d-o-hub/github-template-ai-agents/eu-ai-act-compliance"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/eu-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/d-o-hub/github-template-ai-agents/eu-ai-act-compliance"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/eu-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 | $0.00072 | $0.00925 |
| Opus 5 | $0.00036 | $0.00463 |
| Sonnet 5 | $0.00014 | $0.00185 |
| Haiku 4.5 | $0.00007 | $0.00093 |
Grade A, and why
eu-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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
EU AI Act Compliance
When to Use
- User asks to ensure EU AI Act compliance for logging or transparency
- Need to implement human oversight or record-keeping per Regulation (EU) 2024/1689
- Even if they just say "add compliance logging" or "make sure this is EU AI Act compliant"
Quick Start
import { AIActLogger } from "./eu-ai-act-compliance";
const logger = new AIActLogger({
systemId: "<PROJECT_ID>",
providerName: "<ORG_NAME>",
riskClassification: "limited_risk",
});
await logger.logOperation({
operation: "ai_inference",
inputData: { source: "user_request", hash: "sha256:abc123..." },
outputData: { result: "example_result", confidence: 0.85 },
humanOversight: { reviewerId: "user_123", decision: "approved", timestamp: new Date().toISOString() },
});
Core Concepts
| Concept | Article | Description |
|---|---|---|
| Automatic Logging | Art. 12 | Record events over system lifetime |
| Transparency | Art. 50 | Disclose AI interaction to users |
| Human Oversight | Art. 14 | Enable human intervention |
| Data Governance | Art. 10 | Document training/validation data |
| Retention | Art. 19 | Keep logs minimum 6 months |
Risk Classification
Limited Risk (Article 50)
Systems interacting with natural persons must:
- Disclose AI interaction at first contact (Art. 50.1).
- Mark synthetic content as AI-generated (Art. 50.2).
High Risk (Chapter III, Articles 8-17)
Systems in Annex III (recruitment, credit scoring, etc.) require:
- Risk management (Art. 9) & Data governance (Art. 10).
- Technical documentation (Art. 11) & Automatic logging (Art. 12).
- Human oversight design (Art. 14) & CE marking (Art. 48).
Logging Requirements (Article 12)
interface AIActLogEntry {
timestamp: string; // ISO 8601
systemId: string;
operation: string;
inputData: { source: string; hash: string; description: string };
outputData: { result: string; confidence?: number; explanation?: string };
humanOversight?: { reviewerId: string; decision: "approved" | "rejected" | "modified"; timestamp: string };
retentionUntil: string; // Min 6 months
}
What ships with it
4 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.
- 11d ago First seen · 113 lines · 72 tokens per session scan A 9c8b50117b2e
eu-ai-act-compliance is a skill published in the GitHub repository d-o-hub/github-template-ai-agents (2 stars, last pushed yesterday), licensed MIT. It adds 72 tokens to every session and 925 once invoked, about $0.0004 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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