How does chain-of-thought prompting improve code quality?

Chain-of-thought forces the AI to process steps sequentially and show its work, which significantly improves accuracy in complex tasks like database query optimization or logic analysis.

When should I use few-shot learning in my prompts?

Few-shot learning is ideal when you need the AI to follow a specific, rigid format or perform complex transformations where providing 3-5 examples is more effective than textual description.

Does this skill help with JSON and tool calling?

Yes, it provides patterns for defining tool parameters and explicit output schemas to ensure that Claude returns valid, machine-parseable data consistently.

What are the benefits of using structured system prompts?

Structured system prompts define clear roles, scopes, and constraints, which reduces hallucinations and ensures the AI adheres to specific output formats and security guidelines.

What are common prompt engineering anti-patterns to avoid?

Common mistakes include using vague instructions like 'be helpful', failing to specify output formats, and using negations without providing alternative positive instructions.

Prompt Engineering Patterns

Name: Prompt Engineering Patterns
Author: micsapp

bymicsapp

0•

学習とドキュメンテーション

Implements advanced prompt engineering frameworks to optimize Claude's reasoning, accuracy, and output structure for complex development tasks.

This skill provides a comprehensive library of industry-standard prompt engineering strategies specifically tailored for Claude Code and AI agents. It enables developers to implement structured system prompts, chain-of-thought reasoning, and few-shot learning patterns that significantly improve the reliability of AI-generated code and analysis. By providing clear templates for tool calling, response formatting, and anti-pattern avoidance, this skill ensures that AI interactions are deterministic, secure, and optimized for professional software engineering workflows.

主な機能

010 GitHub stars

02Structured system prompt templates for role-based task execution

03Comprehensive anti-pattern guide and quality assurance checklist

04Few-shot learning examples for precise natural language to code mapping

05Chain-of-thought patterns to improve logical reasoning and debugging

06Optimized tool and function calling definitions for AI agents

ユースケース

01Creating high-accuracy SQL generation pipelines using few-shot learning examples

02Developing automated code review agents with specific security and performance constraints

03Standardizing AI agent outputs into machine-readable JSON formats for CI/CD integration

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add micsapp/micstec-skills prompt-engineering

For use in Claude.ai and ChatGPT

主な機能

010 GitHub stars

02Structured system prompt templates for role-based task execution

03Comprehensive anti-pattern guide and quality assurance checklist

04Few-shot learning examples for precise natural language to code mapping

05Chain-of-thought patterns to improve logical reasoning and debugging

06Optimized tool and function calling definitions for AI agents

ユースケース

01Creating high-accuracy SQL generation pipelines using few-shot learning examples

02Developing automated code review agents with specific security and performance constraints

03Standardizing AI agent outputs into machine-readable JSON formats for CI/CD integration

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add micsapp/micstec-skills prompt-engineering

For use in Claude.ai and ChatGPT