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understand-sdna

Define agent workflows using the SDNA DSL with LangGraph execution.

Updated Aug 23, 2026
Search Tags:#workflow#ai#agent#orchestration#langgraph#dsl
One-click install
npx skills add https://github.com/sancovp/sanctuary-revolution-alpha --skill understand-sdna
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: understand-sdna
Source: https://github.com/sancovp/sanctuary-revolution-alpha/tree/main/base/sdna/skills/understand-sdna
Command: npx skills add https://github.com/sancovp/sanctuary-revolution-alpha --skill understand-sdna

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a framework for building complex AI agent workflows, enabling typed composition, context threading, and seamless integration with LangGraph.

Core Features & Use Cases

  • Agent Workflow DSL: Define agent behaviors using a clear Domain Specific Language (DSL).
  • LangGraph Integration: Natively compile and execute agent workflows within the LangGraph execution substrate.
  • Composable Agents: Build sequential flows (SDNAF) or optimization loops (SDNA^F) from atomic agent units (SDNAC).
  • Use Case: Develop a multi-agent system where one agent prepares specifications, another generates code based on those specs, and a third evaluates the output, all orchestrated via LangGraph.

Quick Start

Use the understand-sdna skill to build a LangGraph agent workflow that generates code based on a provided specification.

Frequently Asked Questions about understand-sdna

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

FAQPage Schema
How do I build multi-agent AI workflows with LangGraph?▼

You can build multi-agent AI workflows with LangGraph by using a Domain Specific Language (DSL) to define agent behaviors, enabling typed composition and context threading for sequential execution or optimization loops.

What is a DSL for AI agent orchestration and when do I need it?▼

A DSL for AI agent orchestration provides a structured syntax to define complex agent behaviors and typed composition. You need it when building multi-agent systems requiring context threading and human-in-the-loop patterns.

Can I compile sequential execution and optimization loops natively in LangGraph?▼

Yes, this approach natively compiles and executes agent workflows within the LangGraph execution substrate, supporting both sequential execution flows (SDNAF) and optimization loops (SDNA^F) from atomic agent units.

How do I set up a code generation pipeline where one agent evaluates another's output?▼

You can set up this pipeline by composing atomic agent units where one agent prepares specifications, another generates code, and a third evaluates the output, all orchestrated via LangGraph using a defined DSL.

Does this approach support human-in-the-loop patterns for AI agent workflows?▼

Yes, the agent workflow DSL supports human-in-the-loop patterns natively, allowing you to integrate manual intervention and context threading directly within your LangGraph execution substrate.

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