improve-prompt

Generate structured prompt templates with role, context, and output format guidelines.

1|Updated Jun 8, 2024
One-click install
npx skills add https://github.com/michaelmechenko/dotfiles --skill improve-prompt-michaelmechenko
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: improve-prompt
Source: https://github.com/michaelmechenko/dotfiles/tree/main/opencode/skill/improve-prompt
Command: npx skills add https://github.com/michaelmechenko/dotfiles --skill improve-prompt-michaelmechenko

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a structured set of prompt patterns and templates to improve the quality, consistency, and outcome of interactions with large language models.

Core Features & Use Cases

  • Quick Prompt Templates: ready-to-use patterns for Analysis Task, Creative Task, and Technical Task.
  • Enhancement Checklist: ensures roles, context, output format, constraints, examples, and verification.
  • Model-Specific Optimizations: guidance tailored for Claude, GPT, and Gemini.
  • Use Case: design prompts to scaffold complex reasoning, plan multi-step workflows, or review prompt quality across domains.

Quick Start

Create an Analysis Task prompt using the provided Quick Templates to structure role, context, objective, and constraints.

Frequently Asked Questions about improve-prompt

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I optimize prompt design for large language models to get better results?

Optimize prompt design by using structured templates that define explicit roles, context, output formats, constraints, and verification steps. This structured approach ensures consistent, high-quality outcomes from large language models across various tasks.

What is the best way to structure an LLM prompt for a complex data analysis task?

Structure an analysis task prompt by applying quick templates that scaffold role definition, objective setting, and constraints. This ensures the large language model receives the precise context needed for complex data analysis.

Does prompt engineering require different patterns for Claude, GPT, and Gemini?

Prompt engineering requires model-specific optimizations for Claude, GPT, and Gemini. Applying tailored patterns and enhancement checklists ensures each large language model interprets roles, context, and output formats correctly.

How do I review prompt quality before running a multi-step workflow?

Review prompt quality by applying an enhancement checklist that verifies the presence of explicit role definitions, context, output formats, constraints, examples, and verification steps before executing multi-step workflows.

Can I use prompt templates for both creative writing and software engineering tasks?

Prompt templates apply to both creative writing and software engineering tasks. Ready-to-use patterns adapt to diverse domains by structuring the necessary context, constraints, and output requirements for each specific use case.