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 obielin/responsible-ai-skills --skill governance-documentationgit clone --depth 1 https://github.com/obielin/responsible-ai-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/obielin/responsible-ai-skills/governance-documentation)<a href="https://agentmods.dev/skills/obielin/responsible-ai-skills/governance-documentation"><img src="https://agentmods.dev/badge/skills/obielin/responsible-ai-skills/governance-documentation/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/obielin/responsible-ai-skills/governance-documentation"><img src="https://agentmods.dev/badge/skills/obielin/responsible-ai-skills/governance-documentation.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 | $0.00033 | $0.01674 |
| Opus 5 | $0.00016 | $0.00837 |
| Sonnet 5 | $0.00007 | $0.00335 |
| Haiku 4.5 | $0.00003 | $0.00167 |
Grade A, and why
governance-documentation 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 11d 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 — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Governance Documentation
You cannot deploy an AI system without governance documentation. This skill generates the minimum required artefacts. Do not ship without completing every item.
What Must Exist Before Deployment
| Document | Required For | Generated By |
|---|---|---|
| Model Card | All AI systems | This skill — Step 1 |
| Risk Assessment | Tier 2+ systems | This skill — Step 2 |
| ATRS Entry | UK public sector | This skill — Step 3 |
| Incident Response Plan | All production systems | This skill — Step 4 |
| Monitoring Plan | All production systems | This skill — Step 5 |
Step 1: Generate the Model Card
Run the model card generator:
python skills/governance-documentation/scripts/generate_model_card.py \
--name "Your System Name" \
--output docs/model-card.md
Or fill in this template manually:
# Model Card: [System Name]
## System Details
- **Name:**
- **Version:**
- **Date:**
- **Type:** [Classification / Regression / NLP / Generative / Agent]
- **Owner:**
- **Contact:**
## Intended Use
- **Primary use:**
- **Intended users:**
- **Out-of-scope uses:**
## Training Data
- **Source:**
- **Size:**
- **Date range:**
- **Known limitations:**
## Performance
| Metric | Overall | Group A | Group B | Group C |
|---|---|---|---|---|
| Accuracy | | | | |
| F1 | | | | |
| FPR | | | | |
## Limitations
-
-
## Ethical Considerations
- Potential for harm:
- Mitigations:
## Human Oversight
- Who reviews outputs:
- Override mechanism:
- Override rate (target):
Step 2: Complete the Risk Assessment
Answer every question. No blanks.
## AI Risk Assessment — [System Name]
### Impact Classification
- Affected population:
- Decision reversibility: [Easily reversed / Difficult / Irreversible]
- Vulnerable groups affected: [Yes/No — specify]
- Maximum consequence of error:
- Risk Tier: [1 / 2 / 3 / 4]
### Data Risks
- Personal data processed: [Yes/No]
- Special category data: [Yes/No — specify]
- DPIA completed: [Yes/No — date]
- Data minimisation applied: [Yes/No]
### Model Risks
- Bias assessment completed: [Yes/No — date]
- Fairness tests passing: [Yes/No]
- Known failure modes:
1.
2.
- Mitigation for each:
1.
2.
### Operational Risks
- What happens if system is unavailable:
- Manual fallback process:
- Time to restore service:
- Monitoring in place: [Yes/No — describe]
### Residual Risk
- Overall residual risk: [Low / Medium / High / Critical]
- Accepted by (SRO name and date):
What ships with it
1 file 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.
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.
- 11d ago First seen · 246 lines · 33 tokens per session scan A 7aba36256ada
governance-documentation is a skill published in the GitHub repository obielin/responsible-ai-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 33 tokens to every session and 1,674 once invoked, about $0.0002 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 2026-08-31.
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