Agent skill

chain-of-thought

Step-by-step reasoning patterns for complex problem solving

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Install this agent skill to your Project

npx add-skill https://github.com/pluginagentmarketplace/custom-plugin-prompt-engineering/tree/main/skills/chain-of-thought

SKILL.md

Chain-of-Thought Skill

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.

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