Claude Agent SDK for Building AI Agents

If you've used Claude Code, you've seen what an AI agent can actually do: read files, run commands, edit code, figure out the steps to accomplish a task.

And you know it doesn't just help you write code, it takes ownership of problems and works through them the way a thoughtful engineer would.

The

is the same engine, yours to point at whatever problem you want, so you can easily build agents of your own.

It's the infrastructure behind Claude Code, exposed as a library. You get the agent loop, the built-in tools, the context management, basically everything you'd otherwise have to build yourself.

This guide walks through building a code review agent from scratch. By the end, you'll have something that can analyze a codebase, find bugs and security issues, and return structured feedback.

More importantly, you'll understand how the SDK works so you can build whatever you actually need.

Our code review agent will:

1. Analyze a codebase for bugs and security issues

2. Read files and search through code autonomously

3. Provide structured, actionable feedback

4. Track its progress as it works

• Runtime -

• SDK -

• Language - TypeScript • Model - Claude Opus 4.5

If you've built agents with the raw API, you know the pattern: call the model, check if it wants to use a tool, execute the tool, feed the result back, repeat until done. This can get tedious when building anything non-trivial.

The SDK handles that loop:

typescript

// Without the SDK: You manage the loop
let response = await client.messages.create({...});
while (response.stop_reason === "tool_use") {
  const result = yourToolExecutor(response.tool_use);
  response = await client.messages.create({ tool_result: result, ... });
}

// With the SDK: Claude manages it
for await (const message of query({ prompt: "Fix the bug in auth.py" })) {
  console.log(message); // Claude reads files, finds bugs, edits code
}

You also get working tools out of the box:

• Read - read any file in the working directory • Write - create new files • Edit - make precise edits to existing files • Bash - run terminal commands • Glob - find files by pattern • Grep - search file contents with regex • WebSearch - search the web • WebFetch - fetch and parse web pages

You don't have to implement any of this yourself.

1. Node.js 18+ installed

2. An Anthropic API key (

)

Step 1: Install Claude Code CLI

The Agent SDK uses Claude Code as its runtime:

bash

npm install -g @anthropic-ai/claude-code

After installing, run claude in your terminal and follow the prompts to authenticate.

Step 2: Create your project

bash

mkdir code-review-agent && cd code-review-agent
npm init -y
npm install @anthropic-ai/claude-agent-sdk
npm install -D typescript @types/node tsx

Step 3: Set your API key

bash

export ANTHROPIC_API_KEY=your-api-key

Create agent.ts:

typescript

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

async function main() {
  for await (const message of query({
    prompt: "What files are in this directory?",
    options: {
      model: "opus",
      allowedTools: ["Glob", "Read"],
      maxTurns: 250
    }
  })) {
    if (message.type === "assistant") {
      for (const block of message.message.content) {
        if ("text" in block) {
          console.log(block.text);
        }
      }
    }
    
    if (message.type === "result") {
      console.log("\nDone:", message.subtype);
    }
  }
}

main();

Run it:

bash

npx tsx agent.ts

Claude will use the Glob tool to list files and tell you what it found.

The query() function returns an async generator that streams messages as Claude works. Here are the key message types:

typescript

for await (const message of query({ prompt: "..." })) {
  switch (message.type) {
    case "system":
      // Session initialization info
      if (message.subtype === "init") {
        console.log("Session ID:", message.session_id);
        console.log("Available tools:", message.tools);
      }
      break;
      
    case "assistant":
      // Claude's responses and tool calls
      for (const block of message.message.content) {
        if ("text" in block) {
          console.log("Claude:", block.text);
        } else if ("name" in block) {
          console.log("Tool call:", block.name);
        }
      }
      break;
      
    case "result":
      // Final result
      console.log("Status:", message.subtype); // "success" or error type
      console.log("Cost:", message.total_cost_usd);
      break;
  }
}

Now let's build something useful. Create review-agent.ts:

typescript

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

async function reviewCode(directory: string) {
  console.log(`\n🔍 Starting code review for: ${directory}\n`);
  
  for await (const message of query({
    prompt: `Review the code in ${directory} for:
1. Bugs and potential crashes
2. Security vulnerabilities  
3. Performance issues
4. Code quality improvements

Be specific about file names and line numbers.`,
    options: {
      model: "opus",
      allowedTools: ["Read", "Glob", "Grep"],
      permissionMode: "bypassPermissions", // Auto-approve read operations
      maxTurns: 250
    }
  })) {
    // Show Claude's analysis as it happens
    if (message.type === "assistant") {
      for (const block of message.message.content) {
        if ("text" in block) {
          console.log(block.text);
        } else if ("name" in block) {
          console.log(`\n📁 Using ${block.name}...`);
        }
      }
    }
    
    // Show completion status
    if (message.type === "result") {
      if (message.subtype === "success") {
        console.log(`\n✅ Review complete! Cost: $${message.total_cost_usd.toFixed(4)}`);
      } else {
        console.log(`\n❌ Review failed: ${message.subtype}`);
      }
    }
  }
}

// Review the current directory
reviewCode(".");

Testing It Out

Create a file with some intentional issues. Create example.ts:

typescript

function processUsers(users: any) {
  for (let i = 0; i <= users.length; i++) { // Off-by-one error
    console.log(users[i].name.toUpperCase()); // No null check
  }
}

function connectToDb(password: string) {
  const connectionString = `postgres://admin:${password}@localhost/db`;
  console.log("Connecting with:", connectionString); // Logging sensitive data
}

async function fetchData(url) { // Missing type annotation
  const response = await fetch(url);
  return response.json(); // No error handling
}

Run the review:

bash

npx tsx review-agent.ts

Claude will identify the bugs, security issues, and suggest fixes.

For programmatic use, you'll want structured data. The SDK supports JSON Schema output:

typescript

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

const reviewSchema = {
  type: "object",
  properties: {
    issues: {
      type: "array",
      items: {
        type: "object",
        properties: {
          severity: { type: "string", enum: ["low", "medium", "high", "critical"] },
          category: { type: "string", enum: ["bug", "security", "performance", "style"] },
          file: { type: "string" },
          line: { type: "number" },
          description: { type: "string" },
          suggestion: { type: "string" }
        },
        required: ["severity", "category", "file", "description"]
      }
    },
    summary: { type: "string" },
    overallScore: { type: "number" }
  },
  required: ["issues", "summary", "overallScore"]
};

async function reviewCodeStructured(directory: string) {
  for await (const message of query({
    prompt: `Review the code in ${directory}. Identify all issues.`,
    options: {
      model: "opus",
      allowedTools: ["Read", "Glob", "Grep"],
      permissionMode: "bypassPermissions",
      maxTurns: 250,
      outputFormat: {
        type: "json_schema",
        schema: reviewSchema
      }
    }
  })) {
    if (message.type === "result" && message.subtype === "success") {
      const review = message.structured_output as {
        issues: Array<{
          severity: string;
          category: string;
          file: string;
          line?: number;
          description: string;
          suggestion?: string;
        }>;
        summary: string;
        overallScore: number;
      };
      
      console.log(`\n📊 Code Review Results\n`);
      console.log(`Score: ${review.overallScore}/100`);
      console.log(`Summary: ${review.summary}\n`);
      
      for (const issue of review.issues) {
        const icon = issue.severity === "critical" ? "🔴" :
                     issue.severity === "high" ? "🟠" :
                     issue.severity === "medium" ? "🟡" : "🟢";
        console.log(`${icon} [${issue.category.toUpperCase()}] ${issue.file}${issue.line ? `:${issue.line}` : ""}`);
        console.log(`   ${issue.description}`);
        if (issue.suggestion) {
          console.log(`   💡 ${issue.suggestion}`);
        }
        console.log();
      }
    }
  }
}

reviewCodeStructured(".");

By default, the SDK asks for approval before executing tools. You can customize this:

Permission modes

typescript

options: {
  // Standard mode - prompts for approval
  permissionMode: "default",
  
  // Auto-approve file edits
  permissionMode: "acceptEdits",
  
  // No prompts (use with caution)
  permissionMode: "bypassPermissions"
}

Custom permission handler

For fine-grained control, use canUseTool:

typescript

options: {
  canUseTool: async (toolName, input) => {
    // Allow all read operations
    if (["Read", "Glob", "Grep"].includes(toolName)) {
      return { behavior: "allow", updatedInput: input };
    }
    
    // Block writes to certain files
    if (toolName === "Write" && input.file_path?.includes(".env")) {
      return { behavior: "deny", message: "Cannot modify .env files" };
    }
    
    // Allow everything else
    return { behavior: "allow", updatedInput: input };
  }
}

For complex tasks, you can create sp