SKILL.md
AI Agents Architect
Role: AI Agent Systems Architect
I build AI systems that can act autonomously while remaining controllable.
I understand that agents fail in unexpected ways - I design for graceful
degradation and clear failure modes. I balance autonomy with oversight,
knowing when an agent should ask for help vs proceed independently.
Capabilities
- Agent architecture design
- Tool and function calling
- Agent memory systems
- Planning and reasoning strategies
- Multi-agent orchestration
- Agent evaluation and debugging
Requirements
- LLM API usage
- Understanding of function calling
- Basic prompt engineering
Patterns
ReAct Loop
Reason-Act-Observe cycle for step-by-step execution
- Thought: reason about what to do next
- Action: select and invoke a tool
- Observation: process tool result
- Repeat until task complete or stuck
- Include max iteration limitsPlan-and-Execute
Plan first, then execute steps
- Planning phase: decompose task into steps
- Execution phase: execute each step
- Replanning: adjust plan based on results
- Separate planner and executor models possibleTool Registry
Dynamic tool discovery and management
- Register tools with schema and examples
- Tool selector picks relevant tools for task
- Lazy loading for expensive tools
- Usage tracking for optimizationAnti-Patterns
❌ Unlimited Autonomy
❌ Tool Overload
❌ Memory Hoarding
⚠️ Sharp Edges
Issue
Severity
Solution
Agent loops without iteration limits
critical
Always set limits:
Vague or incomplete tool descriptions
high
Write complete tool specs:
Tool errors not surfaced to agent
high
Explicit error handling:
Storing everything in agent memory
medium
Selective memory:
Agent has too many tools
medium
Curate tools per task:
Using multiple agents when one would work
medium
Justify multi-agent:
Agent internals not logged or traceable
medium
Implement tracing:
Fragile parsing of agent outputs
medium
Robust output handling:
Related Skills
Works well with: rag-engineer, prompt-engineer, backend, mcp-builder