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Skeleton of Thoughts(SoT)
Generates a skeleton outline, then expands each point in parallel to cut latency while keeping structure
In 30 seconds
- What
- Generates a skeletal outline of a problem's structure, then expands each branch in parallel to reduce latency while preserving logical organization.
- When to use
- Complex problems with clear hierarchical structure where you need fast answers and can parallelize expansion of independent subtopics.
- Watch out
- Skeleton quality determines output quality; poor initial structure forces rework or produces incoherent expansions across branches.
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Skeleton of Thoughts: Overview
Generates a skeleton outline, then expands each point in parallel to cut latency while keeping structure
- Flexible reasoning scaffolds
- Structured yet adaptable outlines
- Reusable problem-solving templates
- Supports creative reasoning
- Efficient knowledge organization
- Guided but not rigid thinking
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References
The papers, specifications, and repositories this pattern is based on.
- Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation (Ning et al., 2023)arXiv:2307.15337
- Tree of Thoughts: Deliberate Problem Solving with Large Language Models (Yao et al., 2023)arXiv:2305.10601
- Chain-of-Thought Prompting Elicits Reasoning in Large Language Models (Wei et al., 2022)arXiv:2201.11903
- OpenAI Parallel Processing Techniques
- LangChain Parallel Chain Execution
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