agentsop-dify

What problem does it solve?

It solves the problem of turning Dify (a visual LLM application platform) into repeatable, production-ready decision patterns so coder agents and teams can ship LLM apps faster and with fewer architectural mistakes.

Core Features & Use Cases

• Dify platform mental model: Aligns teams on Dify’s five-layer architecture (Studio/Apps/Knowledge/Plugins/Monitoring) and how the unified graph engine executes workflows and chatflows.
• SOP distillation for building LLM apps: Provides a phase-by-phase operating procedure (deploy → prompt → RAG setup → tools/plugins → build → test/publish → monitor → iterate) with explicit decision rules.
• Dilemma cases and anti-pattern boundaries: Covers common failure modes like unmaintainable mega-workflows, missing retrieval testing, misusing code nodes, and hitting throughput/latency ceilings—plus what to do instead.
• Ecosystem positioning: Helps choose between Dify and adjacent tools (Flowise/LangFlow/Coze/RAGFlow/n8n/LangGraph/LlamaIndex/CrewAI) based on constraints.

Quick Start

Ask the agent to produce a Dify SOP for “an internal document Q&A app” including app type choice, knowledge base ingestion plan, and a workflow build order with the recommended monitoring setup.