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STRIDE Analysis Patterns

stride-analysis-patterns

Apply STRIDE methodology to systematically identify threats. Use when analyzing system security, conducting threat modeling sessions, or creating security documentation.

techwavedev/agi-agent-kit0installs4stars

SKILL.md

Full skill instructions

STRIDE Analysis Patterns

Systematic threat identification using the STRIDE methodology.

Use this skill when

  • Starting new threat modeling sessions
  • Analyzing existing system architecture
  • Reviewing security design decisions
  • Creating threat documentation
  • Training teams on threat identification
  • Compliance and audit preparation

Do not use this skill when

  • The task is unrelated to stride analysis patterns
  • 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

Retrieve prior Architecture Decision Records (ADRs), trade-off analyses, and system design rationale. Critical for maintaining consistency across long-running projects.

# Check for prior architecture/​design context before starting
python3 execution/​memory_manager.py auto --query "architecture decisions and trade-off analysis for Stride Analysis Patterns"

Storing Results

After completing work, store architecture/​design decisions for future sessions:

python3 execution/​memory_manager.py store \
  --content "Architecture: event-driven microservices with CQRS, Pulsar for messaging, Qdrant for semantic search" \
  --type decision --project <project> \
  --tags stride-analysis-patterns architecture

Multi-Agent Collaboration

Broadcast architecture decisions to ALL agents so implementation stays aligned with the chosen patterns.

python3 execution/​cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Completed architecture review — ADR documented, trade-offs analyzed, team aligned" \
  --project <project>

Control Tower Coordination

Register architecture tasks in the Control Tower so all agents across machines know the current system design and constraints.

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