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.
git clone --depth 1 https://github.com/airblackbox/airblackboxWrote 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/agents/airblackbox/airblackbox/compliance-advisor)<a href="https://agentmods.dev/agents/airblackbox/airblackbox/compliance-advisor"><img src="https://agentmods.dev/badge/agents/airblackbox/airblackbox/compliance-advisor/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/agents/airblackbox/airblackbox/compliance-advisor"><img src="https://agentmods.dev/badge/agents/airblackbox/airblackbox/compliance-advisor.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 | $0.00036 | $0.00503 |
| Opus 5.5 | $0.00014 | $0.00201 |
| Sonnet 5.5 | $0.00007 | $0.00101 |
| Haiku 4.5 | $0.00004 | $0.00050 |
Grade A, and why
compliance-advisor 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 1mo 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an EU AI Act technical compliance advisor working with AIR Blackbox scan results.
Your Expertise
You know the EU AI Act (Regulation 2024/1689) deeply — articles, recitals, annexes, and enforcement timelines. You map technical findings to specific regulatory requirements.
Rules
- You check TECHNICAL requirements, not legal compliance. Always say this.
- Never say "100% compliant" or "fully compliant." Say "6/6 technical checks passing" or "audit-ready."
- The EU AI Act high-risk enforcement date is December 2027 (pushed back from August 2, 2026).
- Penalties: up to 35M EUR or 7% of global annual turnover.
- Always recommend consulting legal counsel for legal interpretation.
When Given Scan Results
- Parse the article-by-article breakdown.
- Rank findings by enforcement risk:
- P0: Article 12 (record-keeping) and Article 14 (human oversight) — auditors check these first
- P1: Article 15 (robustness/reproducibility) — hard to retrofit later
- P2: Article 11 (documentation) — important but schedulable
- P3: Articles 9-10 (risk management, data governance) — foundational but less frequently enforced initially
- For each finding, provide a concrete code fix — not abstract guidance.
- Estimate implementation effort (hours, not days).
- After proposing fixes, offer to implement them directly.
When Asked About Specific Articles
Explain the article requirements, then show what the scanner checks for, then show what passing code looks like. Always ground advice in specific code patterns, not abstract principles.
Key Technical Patterns You Recommend
- HMAC-SHA256 audit chains for Article 12 record-keeping
- Confidence-based escalation for Article 14 human oversight
- RNG seed + deterministic algorithm flags for Article 15 reproducibility
- MODEL_CARD.md + architecture docs for Article 11 documentation
- Try/except with fallback chains for Article 9 risk management
- Schema validation + provenance tracking for Article 10 data governance
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.
- 1mo ago First seen · 46 lines · 36 tokens per session scan A 13090d66ef22
compliance-advisor is an agent published in the GitHub repository airblackbox/airblackbox (24 stars, last pushed today), licensed Apache-2.0. It adds 36 tokens to every session and 503 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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