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Ai Development Governance
ASecurityAI-augmented development controls, GitHub Copilot governance, LLM security, AI-generated code review per Hack23 Secure Development Policy
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- Added October 17, 2026
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[](https://www.skillsdirectory.com/skills/diegosouzapw-ai-development-governance)---
name: ai-development-governance
description: AI-augmented development controls, GitHub Copilot governance, LLM security, AI-generated code review per Hack23 Secure Development Policy
license: MIT
---
# 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 ๐ค](https://github.com/Hack23/ISMS-PUBLIC/blob/main/Secure_Development_Policy.md#ai-augmented-development-controls)** for responsible AI-assisted development.
## Rules
### 1. AI as Proposal Generator, Not Authority (Policy Section ๐ค.1)
1. **Human Review Required**: All AI-generated code MUST be reviewed by human developer
2. **Understanding Required**: Developer MUST understand what AI-generated code does
3. **No Blind Acceptance**: Never merge AI suggestions without verification
4. **Test AI Code**: All AI-generated code requires tests with 80%+ coverage
5. **Security Review**: AI-generated security code requires additional security review
### 2. PR Review Requirements (Policy Section ๐ค.2)
6. **AI Disclosure**: PRs with significant AI-generated code MUST be labeled
7. **Code Ownership**: Developer submitting PR owns the code, regardless of AI generation
8. **Review Standards**: Same review standards apply to AI-generated and human-written code
9. **Security Validation**: Security-critical AI code requires security team approval
10. **No Bypass**: AI assistance does NOT reduce review requirements
### 3. Curator-Agent as Tooling Change (Policy Section ๐ค.3)
11. **Agent Purpose**: Custom agents provide specialized expertise, not replace human judgment
12. **Skill Integration**: Skills teach patterns, developers validate appropriateness
13. **Agent Transparency**: Document which agents/skills were used
14. **Agent Limitations**: Understand agent limitations and potential biases
15. **Agent Testing**: Test agent-generated code as rigorously as any other code
### 4. Security Requirements (Policy Section ๐ค.4)
16. **No Secrets in Prompts**: Never include secrets, API keys, or credentials in AI prompts
17. **Data Classification**: Don't share classified or sensitive data with AI
18. **Code Review**: AI-generated security controls require expert security review
19. **Vulnerability Scanning**: Run CodeQL/SAST on all AI-generated code
20. **ISMS Compliance**: AI-generated code MUST comply with all ISMS policies
## Examples
### โ
Good Pattern: AI-Generated Code with Proper Review
```typescript
/**
* Search MEPs by country
*
* AI-GENERATED: GitHub Copilot assisted with initial implementation
* REVIEWED-BY: developer@hack23.com
* SECURITY-REVIEWED-BY: security@hack23.com
* TEST-COVERAGE: 95%
*
* ISMS Policy: Secure Development Policy Section ๐ค.1-๐ค.4
* Evidence: https://github.com/Hack23/ISMS-PUBLIC/blob/main/Secure_Development_Policy.md#ai-augmented-development-controls
*
* @param country - ISO 3166-1 alpha-2 country code
* @returns Array of MEPs from specified country
*/
export async function searchMEPsByCountry(country: string): Promise<MEP[]> {
// AI suggested this validation - REVIEWED AND ENHANCED
const CountrySchema = z.string()
.length(2, 'Country code must be 2 characters')
.regex(/^[A-Z]{2}$/, 'Country code must be uppercase')
.refine(
(code) => EU_MEMBER_STATES.has(code),
{ message: 'Not a valid EU member state' }
);
// Human added: Additional security validation
const validatedCountry = CountrySchema.parse(country);
// AI suggested this caching logic - REVIEWED AND APPROVED
const cacheKey = `meps:country:${validatedCountry}`;
const cached = mepCache.get(cacheKey);
if (cached) {
auditLog.record({
eventType: AuditEventType.CACHE_HIT,
subject: cacheKey,
outcome: 'success',
});
return cached;
}
// Human added: Rate limiting (AI didn't suggest this)
await rateLimiter.waitForSlot();
// AI suggested this API call - REVIEWED
const response = await fetch(
`https://data.europarl.europa.eu/api/v2/meps?country=${validatedCountry}`,
{
headers: {
'Accept': 'application/json',
'User-Agent': 'European-Parliament-MCP-Server/1.0',
},
}
);
// Human added: Comprehensive error handling
if (!response.ok) {
auditLog.recordAPIError(response.status, validatedCountry);
throw new APIError(`EP API error: ${response.status}`);
}
const meps = await response.json();
// AI suggested caching - REVIEWED AND APPROVED
mepCache.set(cacheKey, meps);
// Human added: GDPR audit logging
auditLog.recordPersonalDataAccess(
'system',
`meps:country:${validatedCountry}`,
'Country-based MEP search'
);
return meps;
}
// AI-GENERATED TESTS - REVIEWED AND ENHANCED
describe('searchMEPsByCountry', () => {
it('should validate country code format', async () => {
// AI suggested this test
await expect(searchMEPsByCountry('USA')).rejects.toThrow('Not a valid EU member state');
});
it('should reject lowercase country codes', async () => {
// Human added this test (AI missed it)
await expect(searchMEPsByCountry('de')).rejects.toThrow('Country code must be uppercase');
});
it('should use cache on subsequent requests', async () => {
// AI suggested this test - ENHANCED
vi.mock('./api', () => ({
fetchMEPs: vi.fn().mockResolvedValue([{ id: 1, country: 'DE' }])
}));
await searchMEPsByCountry('DE');
await searchMEPsByCountry('DE');
const apiMock = await import('./api');
expect(apiMock.fetchMEPs).toHaveBeenCalledTimes(1);
});
it('should log GDPR access', async () => {
// Human added (security-critical test)
const logSpy = vi.spyOn(auditLog, 'recordPersonalDataAccess');
await searchMEPsByCountry('DE');
expect(logSpy).toHaveBeenCalledWith(
'system',
'meps:country:DE',
'Country-based MEP search'
);
});
});
```
**Pull Request Description:**
```markdown
## AI-Generated Code Disclosure
**AI Tool Used**: GitHub Copilot
**AI Contribution**: ~60% (initial implementation, test structure)
**Human Review**: All code reviewed, enhanced security, added GDPR logging
**Security Review**: โ
Approved by security@hack23.com
**Test Coverage**: 95% (4 passing tests)
### Human Enhancements
- Added EU member state validation
- Added rate limiting
- Enhanced error handling
- Added GDPR audit logging
- Added security-focused test case
### Review Checklist
- [x] Code understood and validated
- [x] Security controls verified
- [x] Tests pass with 80%+ coverage
- [x] ISMS compliance validated
- [x] No secrets or sensitive data
- [x] Documentation complete
```
**Policy Reference**: [Secure Development Policy Section ๐ค](https://github.com/Hack23/ISMS-PUBLIC/blob/main/Secure_Development_Policy.md#ai-augmented-development-controls)
### โ
Good Pattern: Custom Copilot Agent with Governance
```markdown
---
name: example-agent
description: Example agent with proper governance
tools: ["view", "edit", "create"]
---
# Example Agent
**AI Governance Notice**: This agent uses AI to generate code suggestions. All suggestions MUST be reviewed by human developers per [Secure Development Policy Section ๐ค](https://github.com/Hack23/ISMS-PUBLIC/blob/main/Secure_Development_Policy.md#ai-augmented-development-controls).
## Core Expertise
You specialize in X, Y, Z.
## Rules
1. **Security First**: All code must follow security-by-design principles
2. **ISMS Compliance**: Reference appropriate ISMS policies
3. **Test Coverage**: Generate tests achieving 80%+ coverage
4. **Human Review**: Remind users to review all generated code
5. **Evidence Links**: Provide evidence links to policy compliance
## Remember
**ALWAYS:**
- โ
Generate code that follows ISMS policies
- โ
Include comprehensive tests
- โ
Document security considerations
- โ
Reference evidence in Hack23 repos
- โ
Remind users to review AI-generated code
**NEVER:**
- โ Include secrets or credentials
- โ Skip input validation
- โ Generate code without tests
- โ Bypass security controls
- โ Claim AI-generated code is perfect
---
**Governance**: This agent's output requires human review per AI Development Governance policy.
```
### โ
Good Pattern: AI Security Validation Checklist
```markdown
# AI-Generated Code Security Review Checklist
**Project**: European Parliament MCP Server
**PR**: #123
**AI Tool**: GitHub Copilot
**Date**: 2026-02-16
## Pre-Merge Security Validation
### Code Understanding
- [ ] Developer understands all AI-generated code
- [ ] Code purpose and logic documented
- [ ] Edge cases identified and handled
### Security Controls
- [ ] Input validation with Zod schemas
- [ ] No hardcoded secrets or credentials
- [ ] Error handling doesn't expose sensitive data
- [ ] Audit logging for security events
- [ ] Rate limiting implemented where needed
### ISMS Compliance
- [ ] Follows security-by-design principles
- [ ] Aligns with threat model
- [ ] Implements defense-in-depth
- [ ] Complies with GDPR (if handling personal data)
- [ ] References appropriate ISMS policies
### Testing
- [ ] Unit tests achieve 80%+ coverage
- [ ] Security test cases included
- [ ] Edge cases tested
- [ ] Error paths tested
- [ ] Integration tests passing
### Code Quality
- [ ] TypeScript strict mode compliant
- [ ] ESLint passing with no warnings
- [ ] Code follows project conventions
- [ ] Documentation complete (JSDoc)
- [ ] No TODO or FIXME comments
### Vulnerability Scanning
- [ ] CodeQL scan passing
- [ ] npm audit shows zero vulnerabilities
- [ ] Dependency licenses approved
- [ ] SAST tools report no issues
## Security Review Sign-Off
- [ ] Reviewed by: ___________________
- [ ] Date: ___________________
- [ ] Security concerns: None / [Document concerns]
- [ ] Approval: โ
Approved / โ Requires changes
## Post-Merge Monitoring
- [ ] Monitor for runtime errors
- [ ] Track performance metrics
- [ ] Review audit logs for anomalies
- [ ] Schedule follow-up review in 30 days
```
**Policy Reference**: [Secure Development Policy Section ๐ค.2](https://github.com/Hack23/ISMS-PUBLIC/blob/main/Secure_Development_Policy.md#pr-review-requirements)
### โ
Good Pattern: AI-Generated Code Documentation
```typescript
/**
* AI-GENERATED CODE DOCUMENTATION
*
* Generation Details:
* - Tool: GitHub Copilot
* - Generation Date: 2026-02-16
* - Prompt: "Create a rate limiter for European Parliament API"
* - AI Contribution: 70% (algorithm, structure)
* - Human Contribution: 30% (security enhancements, tests)
*
* Review Details:
* - Reviewed By: developer@hack23.com
* - Security Review: security@hack23.com
* - Review Date: 2026-02-16
* - Review Notes: Enhanced with audit logging, added comprehensive tests
*
* ISMS Compliance:
* - Policy: Secure Development Policy Section ๐ค
* - Controls: Rate limiting (DoS prevention), Audit logging
* - Evidence: https://github.com/Hack23/ISMS-PUBLIC/blob/main/Secure_Development_Policy.md
*
* Test Coverage: 95%
* Security Tests: 3 test cases
* Performance Tests: 2 test cases
*/
export class EPAPIRateLimiter {
// Implementation...
}
```
## Anti-Patterns
### โ Bad: Blindly Accepting AI Code
```typescript
// GitHub Copilot suggested this - looks good, merging!
export async function handleUserData(data: any) {
return await processData(data); // No validation!
}
```
**Why**: Violates AI Development Governance - no review, no validation, no tests
### โ Bad: Including Secrets in AI Prompts
```
Prompt to Copilot: "Create API client with API key abc123xyz456"
```
**Why**: Violates Policy Section ๐ค.4 - Never share secrets with AI
### โ Bad: No AI Disclosure
```markdown
# Pull Request
Changed the search function.
```
**Why**: Violates transparency - significant AI-generated code must be disclosed
## Evidence Portfolio
### Reference Implementations
1. **European Parliament MCP Server**
- Custom Agents: https://github.com/Hack23/European-Parliament-MCP-Server/tree/main/.github/agents
- AI Skills: https://github.com/Hack23/European-Parliament-MCP-Server/tree/main/.github/skills
- Agent Guide: https://github.com/Hack23/European-Parliament-MCP-Server/blob/main/AGENTS_AND_SKILLS_GUIDE.md
2. **Citizen Intelligence Agency (CIA)**
- AI Governance: https://github.com/Hack23/cia/blob/master/AI_DEVELOPMENT_GOVERNANCE.md
3. **Black Trigram Game**
- Copilot Agents: https://github.com/Hack23/blacktrigram/tree/main/.github/agents
### Policy Documents
- **Secure Development Policy Section ๐ค**: https://github.com/Hack23/ISMS-PUBLIC/blob/main/Secure_Development_Policy.md#ai-augmented-development-controls
- **AI Development Guidelines**: Best practices for AI-assisted development
## GitHub Copilot Integration
### Custom Agents Best Practices
1. **Clear Purpose**: Each agent has specific expertise
2. **Security Focus**: Security controls in all agent instructions
3. **Evidence Links**: Reference Hack23 repos for patterns
4. **Human Review Reminder**: Always remind users to review
5. **ISMS Alignment**: All agents reference ISMS policies
### Skills Best Practices
1. **Pattern-Based**: Teach patterns, not specific solutions
2. **Auto-Activation**: Skills activate based on context
3. **Evidence-Backed**: Include working examples from real repos
4. **Compliance-Focused**: Map patterns to ISMS policies
5. **Test-Driven**: Include testing patterns
## AI Development Checklist
- [ ] AI tool disclosed in PR description
- [ ] AI-generated code percentage estimated
- [ ] All AI code reviewed and understood
- [ ] Security controls validated
- [ ] Tests achieve 80%+ coverage
- [ ] ISMS compliance verified
- [ ] No secrets in code or prompts
- [ ] Documentation includes AI disclosure
- [ ] Security review completed (if security-critical)
- [ ] CodeQL/SAST passing
- [ ] Appropriate ISMS policies referenced
## ISMS Compliance
This skill enforces:
- **AI-001**: AI as proposal generator principle
- **AI-002**: PR review requirements for AI code
- **AI-003**: Custom agent governance
- **AI-004**: AI security requirements
**Policy Reference**: [Hack23 Secure Development Policy Section ๐ค](https://github.com/Hack23/ISMS-PUBLIC/blob/main/Secure_Development_Policy.md#ai-augmented-development-controls)
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