Get structured output from agents

import { query } from "@anthropic-ai/claude-agent-sdk";

// Define the shape of data you want back
const schema = {
  type: "object",
  properties: {
    company_name: { type: "string" },
    founded_year: { type: "number" },
    headquarters: { type: "string" }
  },
  required: ["company_name"]
};

for await (const message of query({
  prompt: "Research Anthropic and provide key company information",
  options: {
    outputFormat: {
      type: "json_schema",
      schema: schema
    }
  }
})) {
  // The result message contains structured_output with validated data
  if (message.type === "result" && message.structured_output) {
    console.log(message.structured_output);
    // { company_name: "Anthropic", founded_year: 2021, headquarters: "San Francisco, CA" }
  }
}

import { z } from "zod";
import { query } from "@anthropic-ai/claude-agent-sdk";

// Define schema with Zod
const FeaturePlan = z.object({
  feature_name: z.string(),
  summary: z.string(),
  steps: z.array(z.object({
    step_number: z.number(),
    description: z.string(),
    estimated_complexity: z.enum(["low", "medium", "high"])
  })),
  risks: z.array(z.string())
});

type FeaturePlan = z.infer<typeof FeaturePlan>

// Convert to JSON Schema
const schema = z.toJSONSchema(FeaturePlan);

// Use in query
for await (const message of query({
  prompt: "Plan how to add dark mode support to a React app. Break it into implementation steps.",
  options: {
    outputFormat: {
      type: "json_schema",
      schema: schema
    }
  }
})) {
  if (message.type === "result" && message.structured_output) {
    // Validate and get fully typed result
    const parsed = FeaturePlan.safeParse(message.structured_output);
    if (parsed.success) {
      const plan: FeaturePlan = parsed.data;
      console.log(`Feature: ${plan.feature_name}`);
      console.log(`Summary: ${plan.summary}`);
      plan.steps.forEach(step => {
        console.log(`${step.step_number}. [${step.estimated_complexity}] ${step.description}`);
      });
    }
  }
}

import { query } from "@anthropic-ai/claude-agent-sdk";

// Define structure for TODO extraction
const todoSchema = {
  type: "object",
  properties: {
    todos: {
      type: "array",
      items: {
        type: "object",
        properties: {
          text: { type: "string" },
          file: { type: "string" },
          line: { type: "number" },
          author: { type: "string" },
          date: { type: "string" }
        },
        required: ["text", "file", "line"]
      }
    },
    total_count: { type: "number" }
  },
  required: ["todos", "total_count"]
};

// Agent uses Grep to find TODOs, Bash to get git blame info
for await (const message of query({
  prompt: "Find all TODO comments in this codebase and identify who added them",
  options: {
    outputFormat: {
      type: "json_schema",
      schema: todoSchema
    }
  }
})) {
  if (message.type === "result" && message.structured_output) {
    const data = message.structured_output;
    console.log(`Found ${data.total_count} TODOs`);
    data.todos.forEach(todo => {
      console.log(`${todo.file}:${todo.line} - ${todo.text}`);
      if (todo.author) {
        console.log(`  Added by ${todo.author} on ${todo.date}`);
      }
    });
  }
}

for await (const msg of query({
  prompt: "Extract contact info from the document",
  options: {
    outputFormat: {
      type: "json_schema",
      schema: contactSchema
    }
  }
})) {
  if (msg.type === "result") {
    if (msg.subtype === "success" && msg.structured_output) {
      // Use the validated output
      console.log(msg.structured_output);
    } else if (msg.subtype === "error_max_structured_output_retries") {
      // Handle the failure - retry with simpler prompt, fall back to unstructured, etc.
      console.error("Could not produce valid output");
    }
  }
}