strands-agents/agent-sop

What it solves

AI agents often struggle with complex, multi-step tasks because they don't have a structured way to follow consistent procedures. Agent SOPs solve this by providing markdown-based instruction sets that break down workflows into clear steps with constraints (MUST, SHOULD, MAY) and parameterized inputs. This makes agent behavior repeatable, shareable, and reliable across different AI systems.

How it works

Each SOP is a markdown file with sections like Overview, Parameters, Steps, and Constraints. Parameters allow the same SOP to be reused with different inputs. Steps use RFC 2119 keywords to control how strictly the agent must follow each instruction. The package (strands-agents-sops) can also convert these SOPs into other formats: MCP server prompts (for tools like Kiro CLI and Claude Code), Cursor IDE commands, and Agent Skills (SKILL.md files) for Claude and compatible agents. This lets you load only the relevant workflow when needed (progressive disclosure).

Who it’s for

Developers and teams who use AI agents (like coding agents) and want them to perform complex tasks—code implementation, codebase analysis, planning, evaluation—with consistent quality. It’s useful for anyone setting up agent-based development workflows and wanting to share them across projects and tools.

Highlights

• Markdown-based SOP format with clear objectives, parameterized inputs, step-by-step instructions, and examples.
• RFC 2119 constraints (MUST, SHOULD, MAY) give precise control without rigid scripting.
• Ships with ready-made SOPs: codebase-summary, pdd, code-task-generator, code-assist, and eval.
• Can be served as MCP prompts, converted to Cursor commands, or generated as Agent Skills.
• External SOPs can be loaded from your own directories (.sop.md files) with first-wins override.
• A defined directory structure (.agents/) organizes outputs from the PDD family of SOPs for easy committing and context pinning.