| name | ai-agent-builder |
| description | Build an AI agent with tools, memory, and multi-step reasoning. Use when the user wants a chatbot, reasoning agent, or multi-agent system. |
| license | MIT |
| compatibility | claude-code opencode github-copilot devin pi cursor |
AI Agent Builder
Design and build an AI agent that uses tools, memory, and reasoning.
Agent types
- Reactive: single-turn, no memory. Use for classification or simple Q&A.
- Conversational: multi-turn with conversation memory. Use for chatbots.
- Tool-using: calls external APIs. Use for actions and lookups.
- Reasoning: plans and executes multiple steps. Use for complex tasks.
- Multi-agent: specialized agents collaborating. Use for workflows.
Tool design
- Clear, action-oriented names.
- Zod or Pydantic input schemas with constraints and examples.
- Concise descriptions that explain when to use the tool.
- Group related tools under a consistent prefix.
Memory patterns
- Buffer memory: keep last N messages.
- Summary memory: summarize older turns to stay within context.
- Vector memory: retrieve relevant facts semantically.
- Entity memory: track entities mentioned across the conversation.
Reasoning
- ReAct: thought, action, observation, repeat.
- Planning: plan first, execute each step, then synthesize.
Always keep the agent's goal visible. Let it ask for missing information before acting.
Output
For a new agent, produce:
- Architecture diagram or description.
- List of tools with inputs and outputs.
- System prompt.
- Conversation flow example.
- Deployment/integration notes.
Guardrails
- Never make up credentials or endpoints.
- Escalate to human when confidence is low or stakes are high.
- Keep tools read-only until the user explicitly approves writes.
