thought-based-reasoning

Original：🇺🇸 English

Not Translated

Use when tackling complex reasoning tasks requiring step-by-step logic, multi-step arithmetic, commonsense reasoning, symbolic manipulation, or problems where simple prompting fails - provides comprehensive guide to Chain-of-Thought and related prompting techniques

1installs

Sourcezpankz/mcp-skillset

Added on2026-02-11

NPX Install

npx skill4agent add zpankz/mcp-skillset thought-based-reasoning

SKILL.md Content

Thought-Based Reasoning Techniques for LLMs

Overview

Chain-of-Thought (CoT) prompting and its variants encourage LLMs to generate intermediate reasoning steps before arriving at a final answer, significantly improving performance on complex reasoning tasks. These techniques transform how models approach problems by making implicit reasoning explicit.

Quick Reference

Technique	When to Use	Complexity	Accuracy Gain
Zero-shot CoT	Quick reasoning, no examples available	Low	+20-60%
Few-shot CoT	Have good examples, consistent format needed	Medium	+30-70%
Self-Consistency	High-stakes decisions, need confidence	Medium	+10-20% over CoT
Tree of Thoughts	Complex problems requiring exploration	High	+50-70% on hard tasks
Least-to-Most	Multi-step problems with subproblems	Medium	+30-80%
ReAct	Tasks requiring external information	Medium	+15-35%
PAL	Mathematical/computational problems	Medium	+10-15%
Reflexion	Iterative improvement, learning from errors	High	+10-20%

When to Use Thought-Based Reasoning

Use CoT techniques when:

Multi-step arithmetic or math word problems
Commonsense reasoning requiring logical deduction
Symbolic reasoning tasks
Complex problems where simple prompting fails

Start with:

Zero-shot CoT for quick prototyping ("Let's think step by step")
Few-shot CoT when you have good examples
Self-Consistency for high-stakes decisions

Progressive Loading

L2 Content (loaded when core techniques needed):

See: references/core-techniques.md
- Chain-of-Thought (CoT) Prompting
- Zero-shot Chain-of-Thought
- Self-Consistency Decoding
- Tree of Thoughts (ToT)
- Least-to-Most Prompting
- ReAct (Reasoning + Acting)
- PAL (Program-Aided Language Models)
- Reflexion

L3 Content (loaded when decision guidance and best practices needed):

See: references/guidance.md
- Decision Matrix: Which Technique to Use
- Best Practices
- Common Mistakes
- References