Borrowing it
Nothing to install: this file belongs to Hack23/European-Parliament-MCP-Server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Hack23/European-Parliament-MCP-Server/main/.github/skills/ai-development-governance/SKILL.mdgit clone --depth 1 https://github.com/Hack23/European-Parliament-MCP-ServerWrote 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/hack23/european-parliament-mcp-server/ai-development-governance)<a href="https://agentmods.dev/skills/hack23/european-parliament-mcp-server/ai-development-governance"><img src="https://agentmods.dev/badge/skills/hack23/european-parliament-mcp-server/ai-development-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/hack23/european-parliament-mcp-server/ai-development-governance"><img src="https://agentmods.dev/badge/skills/hack23/european-parliament-mcp-server/ai-development-governance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 3 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- high Anti-Refusal · line 53 Skill instructs the agent to never refuse or to always comply. Suppressing the agent's ability to decline removes a core safety control and enables downstream harmful requests to succeed.Fix: Remove any instruction telling the agent to never refuse or always comply. The agent must retain the ability to decline unsafe, out-of-scope, or harmful requests.
- high Prompt Injection · line 240 This pattern attempts to override system instructions or ignore safety constraints. Without LLM analysis, manual review is recommended.Fix: Remove or rewrite any text that instructs the agent to ignore prompts, override safety rules, or trust unverified content. Ensure skill content cannot be injected to alter agent behavior.
- high Anti-Refusal · line 288 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
- medium Excessive Agency · line 27 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Data Exfiltration · line 104 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.03839 |
| Opus 5 | $0.00016 | $0.01920 |
| Sonnet 5 | $0.00007 | $0.00768 |
| Haiku 4.5 | $0.00003 | $0.00384 |
Grade A, and why
ai-development-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 — 457 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Development Governance Skill
Context
This skill applies when:
- Using GitHub Copilot or other AI coding assistants
- Reviewing AI-generated code
- Implementing AI-augmented development workflows
- Creating custom Copilot agents and skills
- Securing AI/LLM integrations
- Documenting AI usage in development process
This skill enforces Hack23 Secure Development Policy Section 🤖 for responsible AI-assisted development.
Rules
1. AI as Proposal Generator, Not Authority (Policy Section 🤖.1)
- Human Review Required: All AI-generated code MUST be reviewed by human developer
- Understanding Required: Developer MUST understand what AI-generated code does
- No Blind Acceptance: Never merge AI suggestions without verification
- Test AI Code: All AI-generated code requires tests with 80%+ coverage
- Security Review: AI-generated security code requires additional security review
2. PR Review Requirements (Policy Section 🤖.2)
- AI Disclosure: PRs with significant AI-generated code MUST be labeled
- Code Ownership: Developer submitting PR owns the code, regardless of AI generation
- Review Standards: Same review standards apply to AI-generated and human-written code
- Security Validation: Security-critical AI code requires security team approval
- No Bypass: AI assistance does NOT reduce review requirements
3. Curator-Agent as Tooling Change (Policy Section 🤖.3)
- Agent Purpose: Custom agents provide specialized expertise, not replace human judgment
- Skill Integration: Skills teach patterns, developers validate appropriateness
- Agent Transparency: Document which agents/skills were used
- Agent Limitations: Understand agent limitations and potential biases
- Agent Testing: Test agent-generated code as rigorously as any other code
4. Security Requirements (Policy Section 🤖.4)
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 · 457 lines · 33 tokens per session scan A fdcee4ba82b4
ai-development-governance is a skill published in the GitHub repository Hack23/European-Parliament-MCP-Server (28 stars, last pushed yesterday), licensed Apache-2.0. It adds 33 tokens to every session and 3,839 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 2026-08-30.
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