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 agentmods add skills/librefang/librefang-registry/compliancenpx skills add librefang/librefang-registry --skill compliancegit clone --depth 1 https://github.com/librefang/librefang-registryWrote 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/librefang/librefang-registry/compliance)<a href="https://agentmods.dev/skills/librefang/librefang-registry/compliance"><img src="https://agentmods.dev/badge/skills/librefang/librefang-registry/compliance.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 | $0.00022 | $0.00679 |
| Opus 5 | $0.00011 | $0.00340 |
| Sonnet 5 | $0.00004 | $0.00136 |
| Haiku 4.5 | $0.00002 | $0.00068 |
Grade A, and why
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 4d 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
95% identical to compliance — 3 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 — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compliance Expert
A governance, risk, and compliance specialist with hands-on experience implementing SOC 2, GDPR, HIPAA, and PCI-DSS programs across startups and enterprises. This skill provides actionable guidance for building compliance programs that satisfy auditors while remaining practical for engineering teams, covering policy development, technical controls, evidence collection, and audit preparation.
Key Principles
- Compliance is a continuous process, not a one-time audit; embed controls into daily operations, CI/CD pipelines, and infrastructure-as-code
- Map each regulatory requirement to specific technical controls and designated owners; unowned controls inevitably drift out of compliance
- Apply privacy by design: collect only the data you need, for a stated purpose, and retain it only as long as necessary
- Maintain a risk register that is reviewed quarterly; compliance frameworks require demonstrable risk assessment and mitigation activities
- Document everything: policies, procedures, exceptions, and evidence of control execution; auditors need proof that controls are operating effectively
Techniques
- Implement SOC 2 Type II controls across the five trust service criteria: security, availability, processing integrity, confidentiality, and privacy
- Map GDPR requirements to technical implementations: consent management for lawful basis, data subject access request (DSAR) workflows, and Data Protection Impact Assessments (DPIAs) for high-risk processing
- Enforce HIPAA safeguards: encrypt PHI at rest and in transit, execute Business Associate Agreements (BAAs) with all vendors handling PHI, and apply minimum necessary access controls
- Satisfy PCI-DSS requirements: complete the appropriate Self-Assessment Questionnaire (SAQ), implement network segmentation between cardholder data environments and general networks, and maintain quarterly vulnerability scans
- Build automated audit trails that capture who did what, when, and from where for every access to sensitive data or configuration change
- Define data retention schedules per data category with automated enforcement through TTL policies, scheduled deletion jobs, or archival workflows
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.
- 4d ago First seen · 42 lines · 22 tokens per session scan A faaabdbc3a2f
compliance is a skill published in the GitHub repository librefang/librefang-registry (11 stars, last pushed 10d ago), licensed MIT. It adds 22 tokens to every session and 679 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to compliance, differing in 3 lines, and is treated as a copy.
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Validate a set of engineering artifacts against governance rules and emit a deterministic pass/fail audit report with a compliance score. Trigger on: governance check, compliance audit, validate spec, gate, review compliance.
meta-compliance-audit-bundle
Auditable compliance bundle: deep-research with citations → signable .docx report → read-only PDF archive → memory note of audit findings.
speckit-review-code
General code quality review — project guideline compliance, bug detection, code quality analysis.
continual-learning
Nightly refinement of an existing per-repo review-style prompt using this reviewer's own finding outcomes. Read confirmed (resolved-by-commit / thumbs-up) and dismissed (thumbs-down) findings, promote the bug patterns the team actually fixes, demote the false-positive patterns, reconcile against the current prompt…
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Deterministic OpenRouter image generation adapter for Nano Banana Pro / Gemini image models. Use as skillexec when a meta-skill needs local image files and structured IMAGEREADY records without spawning an LLM agent.