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security-requirement-extraction

Derive security requirements from threat models and business context. Use when translating threats into actionable requirements, creating security user stories, or building security test cases.

techwavedev/agi-agent-kit0installs4stars

SKILL.md

Full skill instructions

Security Requirement Extraction

Transform threat analysis into actionable security requirements.

Use this skill when

  • Converting threat models to requirements
  • Writing security user stories
  • Creating security test cases
  • Building security acceptance criteria
  • Compliance requirement mapping
  • Security architecture documentation

Do not use this skill when

  • The task is unrelated to security requirement extraction
  • You need a different domain or tool outside this scope

Instructions

  • Clarify goals, constraints, and required inputs.
  • Apply relevant best practices and validate outcomes.
  • Provide actionable steps and verification.
  • If detailed examples are required, open resources/​implementation-playbook.md.

Resources

  • resources/​implementation-playbook.md for detailed patterns and examples.
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AGI Framework Integration

Adapted for @techwavedev/​agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Cache compliance check results to avoid re-running expensive AWS API calls. Retrieve prior audit findings to track remediation progress across sessions.

# Check for prior security context before starting
python3 execution/​memory_manager.py auto --query "prior security audit results for Security Requirement Extraction"

Storing Results

After completing work, store security decisions for future sessions:

python3 execution/​memory_manager.py store \
  --content "Audit findings: 3 critical IAM misconfigurations found and remediated" \
  --type technical --project <project> \
  --tags security-requirement-extraction security

Multi-Agent Collaboration

Share security findings with other agents so they avoid introducing vulnerabilities in their code changes.

python3 execution/​cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Completed security audit — 3 critical findings fixed, compliance score 94%" \
  --project <project>

Signed Audit Trail

All security findings are cryptographically signed with the agent's Ed25519 identity, providing tamper-proof audit logs for compliance reporting.

Semantic Cache for Compliance

Cache compliance check results (semantic_cache.py) to avoid redundant AWS API calls. Cache hit at similarity >0.92 returns prior results instantly.

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