Chain-of-Thought Skill

Name: chain-of-thought
Rating: 92
Author: pluginagentmarketplace

Bonded to: chain-of-thought-agent

Quick Start

bash

Skill("custom-plugin-prompt-engineering:chain-of-thought")

Parameter Schema

yaml

parameters:
  cot_type:
    type: enum
    values: [zero_shot, few_shot, self_consistency, tree_of_thought]
    default: zero_shot

  verbosity:
    type: enum
    values: [minimal, standard, detailed]
    default: standard

  verification:
    type: boolean
    default: true
    description: Include self-verification step

CoT Variants

Variant	Description	Accuracy	Token Cost
Zero-shot CoT	"Let's think step by step"	Good	Low
Few-shot CoT	Examples with reasoning	Better	Medium
Self-consistency	Multiple paths, vote	Best	High
Tree-of-Thought	Branch and evaluate	Best	Highest

Core Patterns

1. Zero-Shot Chain-of-Thought

markdown

[Problem statement]

Let's think step by step.

Trigger phrases:

•"Let's think step by step"
•"Let's work through this systematically"
•"Let me break this down"
•"Let's solve this step by step"

2. Few-Shot Chain-of-Thought

markdown

Q: [Example problem 1]
A: Let's think step by step.
   Step 1: [reasoning]
   Step 2: [reasoning]
   Step 3: [reasoning]
   Therefore, the answer is: [answer]

Q: [Example problem 2]
A: Let's think step by step.
   Step 1: [reasoning]
   Step 2: [reasoning]
   Therefore, the answer is: [answer]

Q: [Actual problem]
A: Let's think step by step.

3. Self-Consistency

yaml

process:
  1_generate: "Generate N reasoning paths (temperature > 0)"
  2_extract: "Extract final answer from each path"
  3_vote: "Select answer with highest frequency"
  4_confidence: "Confidence = frequency / N"

parameters:
  n_paths: 5
  temperature: 0.7
  selection: majority_vote

4. Plan-and-Solve

markdown

Q: [Complex problem]

A: Let's first understand the problem and devise a plan.

## Understanding
[Restate the problem and identify key elements]

## Plan
1. [Step 1 description]
2. [Step 2 description]
3. [Step 3 description]

## Execution
Step 1: [Execute and explain]
Step 2: [Execute and explain]
Step 3: [Execute and explain]

## Verification
[Check if solution satisfies requirements]

## Final Answer
[Conclusion]

Domain-Specific Triggers

yaml

triggers_by_domain:
  mathematics:
    - "Let's solve this step by step, showing all work"
    - "First, let's identify what we know and what we need to find"

  coding:
    - "Let's trace through the logic step by step"
    - "Let me walk through this algorithm"

  logic:
    - "Let's analyze each premise systematically"
    - "Let me reason through this logically"

  analysis:
    - "Let's break this down into components"
    - "Let me examine this from multiple angles"

Validation

yaml

validation_checklist:
  logical_flow:
    - [ ] Each step follows from previous
    - [ ] No logical gaps
    - [ ] No circular reasoning

  completeness:
    - [ ] All sub-problems addressed
    - [ ] Edge cases considered
    - [ ] Assumptions stated

  conclusion:
    - [ ] Follows from final step
    - [ ] Directly answers question
    - [ ] Confidence indicated

Troubleshooting

Issue	Cause	Solution
Skips steps	Steps too obvious	Add intermediate steps
Wrong answer	Error in early step	Add verification at each step
Inconsistent	Single path variance	Use self-consistency
Too verbose	Over-explanation	Use minimal verbosity
Token overflow	Too many steps	Consolidate related steps

Integration

yaml

integrates_with:
  - few-shot-prompting: Examples with reasoning
  - prompt-design: Base structure
  - self-reflection: Verify reasoning

combination_patterns:
  cot_plus_few_shot: "Examples showing reasoning steps"
  cot_plus_self_consistency: "Multiple reasoning paths"
  cot_plus_verification: "Reasoning with self-check"

References

See references/GUIDE.md for advanced CoT techniques. See assets/config.yaml for configuration options.