API Patterns

API Patterns

API design principles and decision-making for 2025. Learn to THINK, not copy fixed patterns.

🎯 Selective Reading Rule

Read ONLY files relevant to the request! Check the content map, find what you need.

📑 Content Map

🔗 Related Skills

✅ Decision Checklist

Before designing an API:

• Asked user about API consumers?
• Chosen API style for THIS context? (REST/GraphQL/tRPC)
• Defined consistent response format?
• Planned versioning strategy?
• Considered authentication needs?
• Planned rate limiting?
• Documentation approach defined?

❌ Anti-Patterns

DON'T:

• Default to REST for everything
• Use verbs in REST endpoints (/getUsers)
• Return inconsistent response formats
• Expose internal errors to clients
• Skip rate limiting

DO:

• Choose API style based on context
• Ask about client requirements
• Document thoroughly
• Use appropriate status codes

Script

AGI Framework Integration

Qdrant Memory Integration

Before executing complex tasks with this skill:

python3 execution/memory_manager.py auto --query "<task summary>"

Decision Tree:

• Cache hit? Use cached response directly — no need to re-process.
• Memory match? Inject context_chunks into your reasoning.
• No match? Proceed normally, then store results:

python3 execution/memory_manager.py store \
  --content "Description of what was decided/solved" \
  --type decision \
  --tags api-patterns <relevant-tags>

Note: Storing automatically updates both Vector (Qdrant) and Keyword (BM25) indices.

Agent Team Collaboration

• Strategy: This skill communicates via the shared memory system.
• Orchestration: Invoked by orchestrator via intelligent routing.
• Context Sharing: Always read previous agent outputs from memory before starting.

Local LLM Support

When available, use local Ollama models for embedding and lightweight inference:

• Embeddings: nomic-embed-text via Qdrant memory system
• Lightweight analysis: Local models reduce API costs for repetitive patterns