techwavedev Security Bluebook Builder
Overview
Build a minimal but real security policy for sensitive apps. The output is a single, coherent Blue Book document using MUST/SHOULD/CAN language, with explicit assumptions, scope, and security gates.
Workflow
1) Gather inputs (ask only if missing)
Collect just enough context to fill the template. If the user has not provided details, ask up to 6 short questions:
- What data classes are handled (PII, PHI, financial, tokens, content)?
- What are the trust boundaries (client/server/third parties)?
- How do users authenticate (OAuth, email/password, SSO, device sessions)?
- What storage is used (DB, object storage, logs, analytics)?
- What connectors or third parties are used?
- Retention and deletion expectations (default + user-initiated)?
If the user cannot answer, proceed with safe defaults and mark TODOs.
2) Draft the Blue Book
Load references/bluebook_template.md and fill it with the provided details. Keep it concise, deterministic, and enforceable.
3) Enforce guardrails
- Do not include secrets, tokens, or internal credentials.
- If something is unknown, write "TODO" plus a clear assumption.
- Fail closed: if a capability is required but unavailable, call it out explicitly.
- Keep scope minimal; do not add features or tools beyond what the user asked for.
4) Quality checks
Confirm the Blue Book includes:
- Threat model (assumptions + out-of-scope)
- Data classification + handling rules
- Trust boundaries + controls
- Auth/session policy
- Token handling policy
- Logging/audit policy
- Retention/deletion
- Incident response mini-runbook
- Security gates + go/no-go checklist
Resources
references/bluebook_template.md
AGI Framework Integration
Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills
Memory-First Protocol
Retrieve prior design decisions (color palettes, typography, spacing scales) to maintain visual consistency across sessions. Cache generated design tokens.
# Check for prior frontend/design context before starting
python3 execution/memory_manager.py auto --query "design system decisions and component patterns for Security Bluebook Builder"
Storing Results
After completing work, store frontend/design decisions for future sessions:
python3 execution/memory_manager.py store \
--content "Design system: adopted 8px grid, Inter font family, HSL color tokens with dark mode support" \
--type decision --project <project> \
--tags security-bluebook-builder frontend
Multi-Agent Collaboration
Share design decisions with backend agents (API contract changes) and QA agents (visual regression baselines).
python3 execution/cross_agent_context.py store \
--agent "<your-agent>" \
--action "Implemented UI components — new design system with accessibility compliance (WCAG 2.1 AA)" \
--project <project>
Design Memory Persistence
Store design system tokens and component decisions in Qdrant so any agent on any platform (Claude, Gemini, Cursor) can retrieve and apply consistent styling.