TypeSpec Create Agent

An AI skill that generates TypeSpec agent definitions for building AI powered service agents, creating type safe agent configurations with tool bindings, conversation models, and protocol definitions using the TypeSpec language.

What Is This?

Overview

This skill creates TypeSpec definitions for AI agent configurations. It generates typed agent specifications including tool declarations, input and output schemas, conversation flow models, and integration contracts. The output defines the agent's capabilities, the tools it can invoke, the data it processes, and the protocols it follows, all expressed in TypeSpec's type safe contract language that compiles to usable schemas and SDKs.

Who Should Use This

Designed for developers building AI agent systems who want formal, type safe contracts for their agent interfaces. Ideal for teams creating multi-agent architectures, organizations standardizing agent capabilities across projects, and developers integrating agents with typed API ecosystems.

Why Use It?

Problems It Solves

AI agents interact with tools, users, and other agents through interfaces that are often defined informally in documentation or code comments. Without typed contracts, tool parameter mismatches cause runtime errors, agent capabilities are unclear to integrators, and multi-agent coordination breaks down due to schema inconsistencies. TypeSpec definitions formalize these interfaces.

Core Highlights

• Agent Specification defines agent capabilities and tool bindings in typed contracts
• Tool Schemas generates input and output types for every tool the agent can invoke
• Conversation Models types the message formats agents use to communicate
• Multi Agent Contracts defines interfaces between cooperating agents
• SDK Generation compiles agent specs into client libraries for integration

How to Use It?

Basic Usage

Describe your agent and receive complete TypeSpec definitions for its interface.

// Generated: agents/research-agent.tsp
import "@typespec/http";

model ResearchQuery {
  topic: string;
  depth: "shallow" | "deep";
  maxSources?: int32 = 5;
}

model ResearchResult {
  summary: string;
  sources: Source[];
  confidence: float64;
}

model Source {
  title: string;
  url: string;
  relevance: float64;
}

@route("/agents/research")
namespace ResearchAgent {
  @post op query(@body input: ResearchQuery): ResearchResult;
  @get op status(@path taskId: string): TaskStatus;
}

Real-World Examples

Multi Agent Orchestration Platform

A team building an agent orchestration system used this skill to define contracts for five specialized agents: research, coding, review, testing, and deployment. The TypeSpec definitions ensured that the orchestrator could route tasks to agents with guaranteed type compatibility.

// Generated: agents/orchestrator.tsp
model AgentTask {
  @key id: string;
  type: "research" | "code" | "review" | "test" | "deploy";
  input: Record<unknown>;
  priority: "low" | "medium" | "high";
}

model AgentResponse {
  taskId: string;
  status: "completed" | "failed" | "pending";
  output: Record<unknown>;
  duration: float64;
}

@route("/orchestrator")
namespace Orchestrator {
  @post op dispatch(@body task: AgentTask): AgentResponse;
  @get op listAgents(): AgentInfo[];
  @get op taskStatus(@path id: string): AgentResponse;
}

Advanced Tips

Define shared model libraries for common agent patterns like task status, error responses, and capability descriptions. Use TypeSpec decorators to annotate agent specific metadata like required permissions and rate limits. Compile agent specs into client SDKs for each team consuming the agent API.

When to Use It?

Use Cases

• Agent Interface Design define formal contracts for AI agent capabilities
• Multi Agent Systems specify typed communication protocols between agents
• Tool Registration create schema definitions for agent tool bindings
• Platform Integration generate SDKs for agent API consumers
• Agent Governance standardize agent interfaces across an organization

Related Topics

When creating TypeSpec agent definitions, these prompts activate the skill:

• "Create a TypeSpec agent definition"
• "Define agent tool schemas in TypeSpec"
• "Generate typed contracts for my AI agent"
• "Build a TypeSpec spec for multi-agent communication"

Important Notes

Requirements

• TypeSpec compiler installed for generating output schemas
• Understanding of agent architecture and tool binding patterns
• Target output format for compilation like OpenAPI or JSON Schema
• Works with any agent framework that can consume typed contracts

Usage Recommendations

Do:

• Define tool schemas rigorously to prevent runtime parameter mismatches
• Version agent contracts so integrators can track capability changes
• Share common models across agents using TypeSpec libraries
• Generate client SDKs from compiled specs for type safe integration

Don't:

• Use untyped Record fields when the structure is known in advance
• Skip error type definitions as agents must communicate failures clearly
• Define agent capabilities informally when TypeSpec contracts are available
• Ignore breaking changes in agent interfaces that affect downstream consumers

Limitations

• TypeSpec agent patterns are emerging and community conventions are still forming
• Complex agent behaviors like state machines may need manual TypeSpec authoring
• Generated schemas define interfaces but not agent implementation logic
• Multi-agent coordination protocols may exceed what static type contracts can express