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agent-sdk-definitions

Programmatic agent definitions for the Claude Agent SDK in TypeScript and Python. Use when creating agents for SDK-based applications rather than filesystem-based Claude Code.

インストール方法を見る

含まれるファイル(2)

  • SKILL.md4.1 KB
  • metadata.json1.5 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Agent SDK Definitions

For SDK-based applications, agents can be defined programmatically instead of as markdown files.

TypeScript Definition

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

const options: ClaudeAgentOptions = {
  // Parent agent needs Task tool to invoke subagents
  allowed_tools: ["Read", "Grep", "Glob", "Edit", "Write", "Bash", "Task"],

  agents: {
    "code-reviewer": {
      description: "Security-focused code reviewer. Use PROACTIVELY for auth code.",
      prompt: `You are a security code reviewer specializing in authentication
and authorization code. You identify vulnerabilities, suggest fixes,
and ensure best practices are followed.

## Focus Areas
- Authentication flows
- Session management
- Input validation
- Access control

## Output Format
Provide findings as:
1. Severity (Critical/High/Medium/Low)
2. Location (file:line)
3. Issue description
4. Recommended fix`,
      tools: ["Read", "Grep", "Glob"],  // Read-only access
      model: "opus"
    },

    "test-runner": {
      description: "Runs tests and analyzes failures. Use when tests need to be executed.",
      prompt: `You run test suites and analyze failures. You identify root causes
and suggest fixes for failing tests.`,
      // Omit tools to inherit all from parent
      model: "sonnet"
    }
  }
};

// Execute with agents
for await (const message of query({
  prompt: "Review the authentication module for security issues",
  options
})) {
  console.log(message);
}

Python Definition

import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions, AgentDefinition

options = ClaudeAgentOptions(
    allowed_tools=["Read", "Grep", "Glob", "Edit", "Write", "Bash", "Task"],

    agents={
        "code-reviewer": AgentDefinition(
            description="Security-focused code reviewer. Use PROACTIVELY for auth code.",
            prompt="""You are a security code reviewer specializing in authentication
and authorization code. You identify vulnerabilities, suggest fixes,
and ensure best practices are followed.

## Focus Areas
- Authentication flows
- Session management
- Input validation
- Access control""",
            tools=["Read", "Grep", "Glob"],
            model="opus"
        ),

        "test-runner": AgentDefinition(
            description="Runs tests and analyzes failures. Use when tests need to be executed.",
            prompt="You run test suites and analyze failures.",
            # tools omitted = inherit all
            model="sonnet"
        )
    }
)

async def main():
    async for message in query(
        prompt="Review the authentication module",
        options=options
    ):
        print(message)

asyncio.run(main())

AgentDefinition Schema

type AgentDefinition = {
  description: string;   // Required: When to invoke (routing key)
  prompt: string;        // Required: System prompt content
  tools?: string[];      // Optional: Allowed tools (omit = inherit all)
  model?: 'sonnet' | 'opus' | 'haiku' | 'inherit';  // Optional: Model override
}

Key Differences from Filesystem Agents

AspectFilesystem (.claude/agents/)SDK (programmatic)
FormatMarkdown with YAML frontmatterTypeScript/Python objects
LoadingAutomatic from directoryPassed in options
PromptMarkdown bodyString in prompt field
Use caseClaude Code CLICustom SDK applications

When to Use SDK Format

  • Building custom agent harnesses
  • Programmatic agent orchestration
  • Dynamic agent creation at runtime
  • CI/CD pipelines with agent tasks
  • Applications embedding Claude agents

Providing Both Formats

When a user may use either approach, provide both:

  1. Markdown file for .claude/agents/{name}.md
  2. SDK definition for programmatic use

This ensures compatibility with both Claude Code CLI and custom SDK applications.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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Configures 2-Agent workflow between PM and implementation roles. Use when user mentions 2-Agent, 2エージェント, PM連携設定, Cursor設定, Cursor連携, 2-agent運用. Do NOT load for: 単独運用, ワークフロー実行, ハンドオフ処理.

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Appends relevant hashtags to journal entries based on content analysis. Intended for LLM execution.

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add-agent

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Add a new AI coding agent to Agent Sandbox. Creates all required files (Dockerfile, templates, CI, docs) and wires the agent into the CLI, proxy, and build system.

日本語の概要は準備中です。原文の説明を表示しています。

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Add a new property to the AI agents database. Use when the user wants to add, create, or introduce a new column, property, field, or feature to track across all agents in the comparison matrix. Handles all four required steps - database updates, groups.json, table display, and GitHub issue templates.

日本語の概要は準備中です。原文の説明を表示しています。

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Add new Agent templates to the meta-agent-skills framework.

日本語の概要は準備中です。原文の説明を表示しています。

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