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.
Best use case
agent-sdk-definitions is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using agent-sdk-definitions should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/agent-sdk-definitions/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How agent-sdk-definitions Compares
| Feature / Agent | agent-sdk-definitions | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# Agent SDK Definitions
For SDK-based applications, agents can be defined programmatically instead of as markdown files.
## TypeScript Definition
```typescript
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
```python
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
```typescript
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
| Aspect | Filesystem (.claude/agents/) | SDK (programmatic) |
|--------|------------------------------|-------------------|
| Format | Markdown with YAML frontmatter | TypeScript/Python objects |
| Loading | Automatic from directory | Passed in options |
| Prompt | Markdown body | String in `prompt` field |
| Use case | Claude Code CLI | Custom 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
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