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 magnus919/agent-skills --skill ai-governancegit clone --depth 1 https://github.com/magnus919/agent-skillsWrote 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/magnus919/agent-skills/ai-governance)<a href="https://agentmods.dev/skills/magnus919/agent-skills/ai-governance"><img src="https://agentmods.dev/badge/skills/magnus919/agent-skills/ai-governance/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/magnus919/agent-skills/ai-governance"><img src="https://agentmods.dev/badge/skills/magnus919/agent-skills/ai-governance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00167 | $0.02587 |
| Opus 5 | $0.00084 | $0.01293 |
| Sonnet 5 | $0.00033 | $0.00517 |
| Haiku 4.5 | $0.00017 | $0.00259 |
Grade A, and why
ai-governance 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 12d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Governance
AI governance is the system an organization uses to decide, before a model is built and while it runs, who is accountable for an AI system, what risk it is allowed to carry, what evidence must gate each lifecycle stage, and how the organization reports and audits that posture. This skill teaches an agent to reason about and operate that system: it is a methodology skill, not a tool manual and not legal or security advice.
Scope: What This Skill Owns
| You own | You don't own |
|---|---|
| Governance principles and how they translate into policy and controls | Drafting or opining on legal interpretation of a regulation |
| The governance operating model: councils, stewards, decision rights, RACI, federated vs. centralized | Data-platform mechanics, pipelines, and lineage tooling internals |
| Risk frameworks: NIST AI RMF, ISO/IEC 42001 & 23894, model-risk tiering, risk registers | Implementing authentication, authorization, or vulnerability fixes |
| Lifecycle stage gates across ideation, build, evaluate, deploy, monitor, retire | CI/CD pipeline and deployment-gate configuration |
| Fairness, bias, transparency, explainability, and accountability controls | Product portfolio/roadmap governance cadences |
| Privacy and data governance for training and operational data | Capital allocation, org structure, or M&A governance |
| GxP AI governance overlay: ALCOA+, data integrity, electronic records, risk-based assurance, QMS interfaces | Legal applicability determinations, validation protocols, SOPs, or quality-system operation |
| LLM/agent safety: prompt injection, excessive agency, red-teaming, supply chain | Host-level or application-level security scanning |
| Regulatory landscape and compliance mapping (as guidance, not advice) | Legal drafting, regulatory filings, or attorney-client work product |
| Third-party and model due diligence, board reporting, audit | Any authoritative statement of "your system is compliant" |
This is a prevention-and-operations methodology: it gives the agent frameworks, decision models, and controls to design and run governance, not a claim that a system is compliant or safe. For every engagement, record the operating model, the risk tier, the evidence that gated each stage, and the accountable owner of each accepted exception.
What ships with it
27 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.
- evals/evals.json 8.9 KB
- pytest.ini 216 B
- README.md 3.8 KB
- references/ai-lifecycle-governance.md 29 KB
- references/fairness-bias-accountability.md 16 KB
- references/foundations-and-principles.md 18 KB
- references/governance-operating-model.md 17 KB
- references/gxp-and-data-integrity.md 14 KB
- references/llm-and-agent-security.md 17 KB
- references/privacy-and-data-governance.md 17 KB
- references/procurement-third-party-and-board-oversight.md 23 KB
- references/regulatory-landscape.md 19 KB
- references/risk-management-and-frameworks.md 16 KB
- references/source-index.md 9.9 KB
- references/transparency-and-explainability.md 18 KB
- research/gxp-ai-governance-brief.md 10 KB
- research/gxp-ai-governance-log.md 7.1 KB
- scripts/governance-maturity.py 7.2 KB runs code
- scripts/test_governance_maturity.py 5.8 KB runs code
- scripts/test_use_case_risk_tier.py 6.9 KB runs code
- scripts/use-case-risk-tier.py 9.3 KB runs code
- templates/board-ai-governance-report.md 7.6 KB
- templates/governance-charter.md 6.9 KB
- templates/model-card.md 7.5 KB
- templates/model-risk-assessment.md 8.4 KB
- templates/third-party-due-diligence.md 8.3 KB
- templates/use-case-intake-form.md 5.6 KB
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.
- 12d ago First seen · 151 lines · 167 tokens per session scan A 1e1b7e073627
ai-governance is a skill published in the GitHub repository magnus919/agent-skills (76 stars, last pushed yesterday), licensed MIT. It adds 167 tokens to every session and 2,587 once invoked, about $0.0008 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.
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