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/commands/airblackbox/airblackbox/evidence)<a href="https://agentmods.dev/commands/airblackbox/airblackbox/evidence"><img src="https://agentmods.dev/badge/commands/airblackbox/airblackbox/evidence.svg" alt="Measured on agentmods" 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 | $0.00014 | $0.00297 |
| Opus 5 | $0.00007 | $0.00148 |
| Sonnet 5 | $0.00003 | $0.00059 |
| Haiku 4.5 | $0.00001 | $0.00030 |
Grade A, and why
evidence 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 7d 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.
What it actually says
/air-evidence
Generate a signed evidence package for regulatory audits.
Steps
- Export the evidence package as JSON:
evidencectl export --secret $GATEWAY_SECRET --output evidence-package.json
- Generate a PDF compliance report:
evidencectl pdf --input evidence-package.json --output evidence-report.pdf --company "Your Company Name"
-
The PDF report includes:
- Cover page with gateway ID, chain integrity status, and time range
- Executive summary with aggregate compliance stats
- Compliance controls table (SOC 2 + ISO 27001) with pass/fail/partial status
- Audit chain verification summary
- Recent audit entries with sequence numbers and record hashes
- HMAC-SHA256 attestation for tamper verification
-
To verify the attestation hasn't been tampered with:
- The attestation field is an HMAC-SHA256 hash of the entire package
- Clear the attestation field, re-hash the JSON with the gateway secret
- If the hashes match, the package is authentic
-
Remind the user:
- This is technical evidence, not a legal compliance certificate
- Pair with legal counsel for regulatory submissions
- The evidence package is signed — any modification breaks the attestation
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.
- 7d ago First seen · 40 lines · 14 tokens per session scan A 4aad92d555d2
evidence is a command published in the GitHub repository airblackbox/airblackbox (22 stars, last pushed 8d ago), licensed Apache-2.0. It adds 14 tokens to every session and 297 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
ai-act-scan
Scan a codebase for EU AI Act compliance evidence and gaps. Produces a dimension-scored report with per-file findings, architecture graph, and prioritized recommendations.
ai-act-article
Show which analyzers, compliance dimensions, and current findings in this codebase map to a specific EU AI Act article.
ai-act-scan-fix
Scan a codebase, then propose concrete remediation (code edits, new files, tests) for the top compliance gaps. Does NOT auto-apply — always shows the plan first.
tcop
Generate a Technology Code of Practice (TCoP) review document for a UK Government technology project.
score
Score vendor proposals against evaluation criteria with persistent structured storage.
ai-act-incidents
Show real-world and research-demonstrated security incidents that map to a scanner dimension, EU AI Act article, or threat category. Surfaces OWASP LLM/ASI, NIST AI RMF, and MITRE ATLAS cross-references alongside published mitigations.