agent-builder

Validate and configure DAPR Agents framework agent definitions and tools.

4|3|Updated Dec 24, 2025
One-click install
npx skills add https://github.com/Sahib-Sawhney-WH/dapr-claude-plugin --skill agent-builder-sahib-sawhney-wh
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: agent-builder
Source: https://github.com/Sahib-Sawhney-WH/dapr-claude-plugin/tree/main/skills/agent-builder
Command: npx skills add https://github.com/Sahib-Sawhney-WH/dapr-claude-plugin --skill agent-builder-sahib-sawhney-wh

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides intelligent guidance for building AI agents with the DAPR Agents framework, validates configuration, suggests patterns, and ensures best practices.

Core Features & Use Cases

  • Agent Configuration Validation: Validates agent setup: required imports, name, role, instructions, model, and tools.
  • Pattern Recommendations: Suggests patterns like AssistantAgent, DurableAgent, AgentService, Multi-Agent.
  • Tool Integration Check: Verifies tool definitions have @tool decorator, docstrings, type validation, and async I/O.
  • Memory & Security Guidance: Recommends memory strategies and environment variable usage for keys.
  • Use Case: Generate a basic AssistantAgent named "customer-agent" with a simple tool.

Quick Start

Ask Claude to generate a basic AssistantAgent named "order-assistant" with role "Customer support assistant" and an instruction that helps users place orders.

Frequently Asked Questions about agent-builder

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate AI agent configuration with DAPR Agents?

DAPR Agents validation checks required imports, agent name, role, instructions, model configuration, tools, and memory strategy. It ensures your agent setup follows framework requirements and best practices before deployment, catching configuration errors early.

What patterns does DAPR Agents support for building AI agents?

DAPR Agents supports AssistantAgent, DurableAgent, AgentService, and Multi-Agent patterns. Each pattern is suited to different scenarios: basic assistants, durable stateful agents, microservices, and coordinated multi-agent workflows.

How do I define tools for DAPR agents?

Tools require @tool decorator, docstrings, type validation, and asynchronous I/O. The framework validates tool definitions and ensures they conform to documentation standards and async patterns for proper integration with agent workflows.

Can I use DAPR Agents for multi-agent workflows?

Yes, DAPR Agents supports Multi-Agent patterns for workflow orchestration. You can build coordinated agent systems with shared tools, memory strategies, and LLM configuration across multiple agents.

What security considerations apply to DAPR agent setup?

DAPR Agents enforces security checks for API keys and recommends environment variable usage. Memory and durability configurations are validated to ensure sensitive credentials are handled properly and not hardcoded.

Does DAPR Agents support decorator-based tool definitions?

Yes, decorator-based tool definitions are supported alongside file creation approaches. The framework validates that @tool decorators are present, tools have proper docstrings, and implement async I/O patterns.