Design cost-efficient AI agent architectures. Use when optimizing token usage, selecting model tiers, budgeting compute costs, implementing caching strategies, or designing plan-and-execute patterns for cost reduction. Covers model tiering (frontier for…
Design and implement multi-agent systems with proven coordination patterns. Use when building agent teams, delegation architectures, inter-agent communication, lead-agent orchestration, or agent swarm coordination. Covers 5 orchestration topologies…
Design safety architectures for AI agents — autonomy tiers, permission zones, command approval gates, secret handling, escalation paths, and observability. Use when building agents that execute code, modify files, access networks, handle credentials, or make…
Design agent memory architectures and context window optimization strategies. Use when building persistent memory systems, context budgeting, dynamic context loading, knowledge retrieval, or managing token limits. Covers three-tier memory (episodic, semantic,…
Design production-grade tool specifications for AI agents. Use when defining tool interfaces, parameter schemas, safety flags, error handling, MCP compatibility, or tool composition rules. Covers three specification formats (XML, JSON Schema, markdown), 6…
Generate, audit, and optimize system prompts for AI agents using 8 proven architectural patterns extracted from 16+ production systems (Kimi, Cursor, Devin, Kiro, Claude Code, v0, Windsurf, Lovable, Replit, Traycer, Manus). Use when creating new agent system…