agent

Agent — AI Agent Development

Activate When

• User invokes /godmode:agent
• User says "build an AI agent", "create an agent", "add tools to my agent"
• User says "design agent memory", "agent keeps looping", "agent safety"
• When building autonomous or semi-autonomous LLM-powered systems
• When /godmode:prompt identifies a need for agentic capabilities (tool use, multi-step reasoning)
• When /godmode:rag needs to be wrapped in an agent loop
• When the orchestrator detects agent frameworks (LangChain, LlamaIndex, CrewAI, AutoGen, custom agent loops) in code

Workflow

Step 1: Agent Discovery & Requirements

Understand what the agent must accomplish:

AGENT DISCOVERY:
Purpose: <what the agent must autonomously accomplish>
Type:
  - Single-agent: One agent with tools (most common)
  - Multi-agent: Multiple specialized agents coordinating
  - Human-in-the-loop: Agent proposes, human approves critical actions

User interaction:
  - Conversational: User chats with agent in real-time
  - Autonomous: Agent runs a task to completion without user input
  - Supervised: Agent asks for confirmation at decision points

Environment:
  - Tools available: <list of APIs, databases, code execution, file systems>
  - External systems: <services the agent will interact with>

If the user hasn't specified, ask: "What should this agent do autonomously? What tools does it need?"

Step 2: Architecture Pattern Selection

Select the agent architecture pattern:

AGENT ARCHITECTURE SELECTION:

Patterns:
| Pattern | Best for |
|--|--|
| ReAct | General-purpose tool use, step-by-step reasoning |
| (Reason + Act) | with tool calls. Simple, effective, well-understood. |
| Plan-and-Execute | Complex tasks needing upfront planning. Planner |
|  | creates step list, executor follows it. Good for |
|  | multi-step tasks with clear decomposition. |
| Reflexion | Tasks requiring self-correction. Agent attempts, |
|  | evaluates own output, and retries with feedback. |