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 msaad00/agent-bom --skill compliancegit clone --depth 1 https://github.com/msaad00/agent-bomWrote 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/msaad00/agent-bom/compliance)<a href="https://agentmods.dev/skills/msaad00/agent-bom/compliance"><img src="https://agentmods.dev/badge/skills/msaad00/agent-bom/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/msaad00/agent-bom/compliance"><img src="https://agentmods.dev/badge/skills/msaad00/agent-bom/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 | $0.00102 | $0.02127 |
| Opus 5.5 | $0.00041 | $0.00851 |
| Sonnet 5.5 | $0.00020 | $0.00425 |
| Haiku 4.5 | $0.00010 | $0.00213 |
Grade A, and why
agent-bom-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 25d 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.
This is a copy
92% identical to agent-bom-compliance — 20 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
agent-bom-compliance — AI Compliance & Policy Engine
Evaluate AI infrastructure scan results against 14 security and regulatory frameworks. Enforce policy-as-code rules. Generate SBOMs in standard formats. Run AISVS v1.0 and CIS benchmark checks.
Install
pipx install agent-bom
agent-bom scan --compliance --compliance-export nist-ai-rmf
agent-bom scan -f cyclonedx -o sbom.json
When to Use
- "compliance report" / "run compliance"
- "NIST" / "NIST AI RMF" / "NIST CSF" / "NIST 800-53"
- "SOC 2" / "SOC2"
- "ISO 27001"
- "OWASP" / "OWASP LLM Top 10" / "OWASP Agentic Top 10"
- "EU AI Act"
- "AISVS" / "AI Security Verification Standard"
- "CMMC" / "FedRAMP"
- "generate SBOM" / "CycloneDX" / "SPDX"
- "policy check" / "policy enforcement"
Tools (5)
| Tool | Description |
|---|---|
compliance |
OWASP LLM/Agentic Top 10, EU AI Act, MITRE ATLAS, NIST AI RMF |
policy_check |
Evaluate results against custom security policy (17 conditions) |
cis_benchmark |
Run CIS benchmark checks against cloud accounts |
generate_sbom |
Generate SBOM (CycloneDX or SPDX format) |
aisvs_benchmark |
OWASP AISVS v1.0 compliance — 9 AI security checks |
Supported Frameworks (15)
- OWASP LLM Top 10 (2025) — prompt injection, supply chain, data leakage
- OWASP MCP Top 10 — MCP-specific security risks
- OWASP Agentic Top 10 — tool poisoning, rug pulls, credential theft
- MITRE ATLAS — adversarial ML threat framework
- MITRE ATT&CK Enterprise — adversary techniques tagged via CWE → CAPEC → ATT&CK on every blast-radius finding
- NIST AI RMF — govern, map, measure, manage lifecycle
- NIST CSF 2.0 — identify, protect, detect, respond, recover
- NIST 800-53 Rev 5 — federal security controls (CM-8, RA-5, SI-2, SR-3)
- FedRAMP Moderate — derived from NIST 800-53 controls
- EU AI Act — risk classification, transparency, SBOM requirements
- ISO 27001:2022 — information security controls (Annex A)
- SOC 2 — Trust Services Criteria
- CIS Controls v8 — implementation groups IG1/IG2/IG3
- CMMC 2.0 — cybersecurity maturity model (Level 1-3)
- PCI DSS v4.0 — payment-card data security requirements
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.
- 25d ago Changed 7df236628760
- 26d ago Changed 3ad8fe10ddfb
- 27d ago Changed a9102e1964f1
- 28d ago Changed b920d2939d5b
- 1mo ago Changed f16d8a9a09b9
- 1mo ago Changed 5818091b26f1
- 1mo ago Changed 3336641e9da2
- 1mo ago Changed e7cd7078c2c2
- 1mo ago Changed 2065e90c4181
- 1mo ago First seen · 197 lines · 102 tokens per session scan A 9fe80d5fa3a9
agent-bom-compliance is a skill published in the GitHub repository msaad00/agent-bom (31 stars, last pushed 25d ago), licensed Apache-2.0. It adds 102 tokens to every session and 2,127 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to agent-bom-compliance, differing in 20 lines, and is treated as a copy.
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