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name: design-patterns description: "Use PocketFlow to design LLM apps and agentic workflows with workflows, agents, RAG, map-reduce, structured output, multi-agent queues, and service/background patterns." metadata: disco-role: operating disable-model-invocation: true license: MIT

PocketFlow Design Patterns

Use this sub-skill when the user wants to turn a task into a PocketFlow application design rather than debug a single node or utility function.

What this sub-skill covers

• Workflow decomposition for article-writing, extraction, planning, and approval flows.
• Agent decision loops and tool/action routing.
• RAG pipelines with offline indexing and online retrieval.
• Map-reduce style document or record processing.
• Structured output with validation-friendly prompts.
• Multi-agent or message-queue style coordination.
• FastAPI/Streamlit/Gradio-style service and background job shapes when they are part of the PocketFlow app structure.
• Cookbook-derived pattern selection and dependency caveats.

What to read first

• Pattern recipes
• Agentic coding guide
• Cookbook map
• Troubleshooting
• Templates

Typical user requests

• "How should I structure this PocketFlow app?"
• "Should I use workflow, agent, or RAG?"
• "How do I add a review/retry loop?"
• "How do I process many docs or files?"
• "How do I design a service-backed or background-job PocketFlow app?"

Route map

Need	Read
Pattern choice and node-level recipe shape	references/pattern-recipes.md
Docs-first process and project skeleton	references/agentic-coding-guide.md
Cookbook-style task matching	references/cookbook-map.md
Architectural failure modes and repair steps	references/troubleshooting.md
Safe local skeleton output	scripts/design_pattern_templates.py

Design principles

1. Start with the smallest useful graph.
2. Put schema and task state into the shared store.
3. Keep exec() focused on compute and utility calls.
4. Use post() to write results and choose the next action.
5. Add validation on outputs that an LLM may produce in an unreliable format.
6. Prefer explicit recipes over clever, over-general node abstractions.

Boundaries

• Do not use this sub-skill for core runtime signatures or retry semantics; read core-abstraction instead.
• Do not use this sub-skill to implement provider-specific LLM wrappers, vector stores, tracing clients, or audio functions; read utilities instead.
• Do not bundle credentialed or network-heavy cookbook scripts. Distill them into safe reusable recipes and note optional dependencies.