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architecture

Modular design, interface stability, dependency management, AI-code health. Triggers: architecture, design, structure, modules, dependencies, coupling, system design.

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hashgraph-online/awesome-codex-plugins
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Files included (6)

  • SKILL.md2.3 KB
  • reference/api-research.md10.7 KB
  • reference/api.md5.7 KB
  • reference/architecture-research.md5.3 KB
  • reference/backend-research.md15.6 KB
  • reference/backend.md4.0 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

<skill id="architecture"> <purpose> Architecture is about managing change over time. Good architecture makes easy things easy and hard things possible. AI-generated code amplifies existing patterns—good or bad. </purpose> <prerequisite> Understand existing codebase structure before proposing changes. Check for established patterns. Follow them unless explicitly changing. </prerequisite> <reference> Skill-specific: skills/architecture/reference/architecture-research.md </reference>

<core_principles>

  1. FOLLOW EXISTING PATTERNS: Don't introduce new patterns without justification.
  2. INTERFACE STABILITY: Changing interfaces breaks everything. Stabilize them first.
  3. MODULAR BOUNDARIES: Clear separation. Each module has one reason to change.
  4. DEPENDENCY DIRECTION: Depend on abstractions, not concretions. Core doesn't know about edges.
  5. SMALLEST CHANGE: Prefer minimal changes that achieve the goal. </core_principles>

<ai_code_health_nexus> From research: 30%+ defect risk when AI applied to unhealthy code. AI amplifies existing patterns. If code is messy, AI makes it messier. Before adding AI to a codebase:

  1. Identify health score (coupling, complexity, test coverage)
  2. Fix critical health issues first
  3. Establish clear interfaces
  4. Then apply AI within those boundaries </ai_code_health_nexus>

<design_heuristics>

  • If you can't explain it simply, the design is too complex
  • Three concrete examples before abstraction
  • Composition over inheritance
  • Make illegal states unrepresentable
  • Parse, don't validate </design_heuristics>

<anti_patterns>

  • Premature abstraction (abstract before 3 concrete uses)
  • Leaky abstractions (implementation details bleeding through)
  • Circular dependencies
  • God objects (one class doing everything)
  • Feature envy (methods that use another class more than their own) </anti_patterns>

<on_complete> agentdb write-end '{"skill":"architecture","decision":"X","coupling_reduced":true,"adr":"path|none"}' </on_complete>

</skill>

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