python-agent-sdk

Create Python AI agents with the Claude Agent SDK.

2|Updated Jul 13, 2025
One-click install
npx skills add https://github.com/krzemienski/shannon --skill python-agent-sdk
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: python-agent-sdk
Source: https://github.com/krzemienski/shannon/tree/main/skills/python-agent-sdk
Command: npx skills add https://github.com/krzemienski/shannon --skill python-agent-sdk

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires claude_agent_sdk, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill solves the problem of building production-ready AI agents with the Claude Agent SDK for Python, providing a comprehensive solution for embedding Claude into pipelines, CI/CD jobs, scheduled tasks, or notebooks.

Core Features & Use Cases

  • Embedded Sub-agent Skills: Sub-agents carry their skills inline; spawning is reliable.
  • Orchestration: Single-message multi-Task dispatch. Sequential, parallel, competitive patterns.
  • Iron Rule Validation: Real-system evidence on disk. No mocks. No stubs. No test files.
  • Meta-judge Consensus: Rubric YAML generated before any judge runs. Hidden thresholds. Debate on disagreement.
  • Self-instrumented: /shannon:doctor and /shannon:audit work — the plugin observes itself.
  • Use Case: For developers and system architects looking to integrate Claude's capabilities into their applications, this Skill offers a robust foundation for building AI agents.

Quick Start

Install the Skill by running the following command: /plugin marketplace add krzemienski/shannon /plugin install shannon@shannon

Frequently Asked Questions about python-agent-sdk

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build production-ready AI agents with the Claude Agent SDK for Python?▼

You can build production-ready AI agents using a Python SDK harness that provides embedded sub-agent skills, orchestration, and iron rule validation. It facilitates integrating Claude into pipelines, CI/CD jobs, scheduled tasks, or notebooks.

What is iron rule validation when creating AI agents with Python?▼

Iron rule validation enforces real-system evidence on disk during agent execution. It rejects mocks, stubs, and test files, ensuring your Python AI agents operate against actual system states rather than simulated environments.

How do I orchestrate multiple Claude agents in a Python pipeline?▼

You orchestrate multiple Claude agents using single-message multi-Task dispatch. The Python SDK supports sequential, parallel, and competitive orchestration patterns to coordinate sub-agents carrying their skills inline.

Does the Claude Agent SDK for Python support MCP servers?▼

Yes, the Claude Agent SDK for Python supports various MCP servers and tools. This allows your production-ready AI agents to connect with external Model Context Protocol servers for extended functionality.

What is meta-judge consensus in AI agent evaluation?▼

Meta-judge consensus generates a rubric YAML file before any judge runs, using hidden thresholds. When judges disagree, it initiates a debate to reach a consensus on the AI agent's output quality.

Do I need the Claude Agent SDK installed to use this Python framework?▼

Yes, the Claude Agent SDK is a required dependency. You must install it to utilize the Python harness for creating production-ready agents with features like orchestration and meta-judge consensus.