Natural language workflows enable AI agents to perform complex, multi-step tasks with consistency and reliability. This project provides "Agent SOPs" (Standard Operating Procedures) in a markdown format, allowing users to define, share, and execute sophisticated workflows across different AI systems. The primary benefit is transforming complex processes into reusable, reliable, and understandable agent behaviors.

How It Works

Agent SOPs are markdown-based instruction sets that define clear objectives, parameterized inputs for flexibility, and step-by-step instructions using RFC 2119 constraints (MUST, SHOULD, MAY) for precise control. This approach allows for reusable, shareable workflows that can be executed by various AI systems, including those using the Python SDK, an MCP Server, or Anthropic Skills, offering a standardized way to manage agent behavior.

Quick Start & Requirements

• Primary Install: pip install strands-agents-sops
• Python SDK Usage: Requires pip install strands-agents strands-agents-tools strands-agents-sops. An example CLI agent is provided.
• MCP Server: Run via strands-agents-sops mcp, with options to load external SOPs using --sop-paths.
• Anthropic Skills: Generate skills using strands-agents-sops skills, with --sop-paths for custom SOPs.
• Prerequisites: Python environment. No specific hardware or CUDA versions are mentioned. Links to documentation, tools, samples, MCP Server, and Agent Builder are indicated but not directly provided in the text.

Highlighted Details

• RFC 2119 Constraints: SOP steps utilize MUST, SHOULD, and MAY keywords for granular control over agent actions, ensuring reliable execution.
• Multi-modal Distribution: SOPs are natively supported via a Python SDK, an MCP Server for tool discovery, and directly integrated with Anthropic's Skills system.
• Context Efficiency for LLMs: When used as Anthropic Skills, SOPs enable progressive disclosure, allowing Claude to intelligently select and load only relevant workflows, preventing context overload.
• AI-Assisted Authoring: New SOPs can be authored rapidly by AI agents, leveraging a provided format rule, making workflow creation accessible.
• Progress Tracking & Resumability: SOPs can instruct agents to document their progress, enhancing transparency and enabling easier resumption of interrupted tasks.

Licensing & Compatibility

• License: Apache License 2.0.
• Compatibility: The Apache 2.0 license is permissive and generally compatible with commercial use and closed-source linking.

Limitations & Caveats

No explicit limitations, alpha status, or known issues are mentioned in the provided README content.