Design complex AI workflows with multiple steps.
Prompt Chain Architect
LangChain, DSPy, Semantic Kernel
Best for
- ▸Multi-document RAG pipeline with sequential summarization and final synthesis
- ▸Complex reasoning workflows requiring chain-of-thought decomposition with verification gates
- ▸Production LLM orchestration with error recovery and context window management
- ▸Task automation requiring parallel processing with conditional branching logic
What you'll get
- ▸Sequential chain architecture with 5 specialized prompts, each with input/output schemas, temperature settings, and JSON validation rules
- ▸Parallel fan-out design for document analysis with merge strategy, error handling, and fallback prompts for failed branches
- ▸Tree-of-thought exploration framework with scoring criteria, pruning logic, and final selection mechanism for complex problem-solving
Complex multi-step tasks requiring LLM orchestration with clear success criteria, error handling requirements, and production constraints.
Complete prompt chain architecture with step-by-step prompts, verification gates, error recovery strategies, and implementation guidance for production deployment.
What's inside
“You are a Prompt Chain Architect. You design, analyze, and optimize multi-step LLM orchestration pipelines for production systems. - Decompose tasks into discrete steps with single responsibilities, explicit I/O contracts (JSON/YAML schemas), and verification gates between them - Integrate failure m...”
Covers
Not designed for ↓
- ×Single-step prompt optimization or basic prompt engineering
- ×Training or fine-tuning LLM models themselves
- ×Real-time conversational AI or chatbot design
- ×Simple automation that doesn't require multi-step LLM orchestration
SupaScore
89.85▼
Evidence Policy
Standard: no explicit evidence policy.
Research Foundation: 8 sources (5 academic, 2 official docs, 1 web)
This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.
Version History
v5.5 final distill
Pipeline v4: rebuilt with 3 helper skills
Initial release via Pipeline v3
Prerequisites
Use these skills first for best results.
Works well with
Need more depth?
Specialist skills that go deeper in areas this skill touches.
Common Workflows
Production RAG Pipeline Development
Design multi-step RAG workflows with retrieval chains, then implement retrieval architecture, establish evaluation metrics, and deploy with monitoring
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