# 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. Use when this capability is needed. - Skill: `tomevault-io/security-requirement-extraction-2` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/security-requirement-extraction-2` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/security-requirement-extraction-2/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/security-requirement-extraction-2 --- # 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. --- ## AGI Framework Integration > **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)** > Original source: [antigravity-awesome-skills](https://github.com/sickn33/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. ```bash # 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: ```bash python3 execution/memory_manager.py store \ --content "Audit findings: 3 critical IAM misconfigurations found and remediated" \ --type technical --project \ --tags security-requirement-extraction security ``` ### Multi-Agent Collaboration Share security findings with other agents so they avoid introducing vulnerabilities in their code changes. ```bash python3 execution/cross_agent_context.py store \ --agent "" \ --action "Completed security audit — 3 critical findings fixed, compliance score 94%" \ --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. --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/techwavedev) — claim your Tome and manage your conversions.