prompt-enhancer
Prompt engineering and optimization for AI/LLMs. Capabilities: transform unclear prompts, reduce token usage, improve structure, add constraints, optimize for specific models, backward-compatible rewrites. Actions: improve, enhance, optimize, refactor, compress prompts. Keywords: prompt engineering, prompt optimization, token efficiency, LLM prompt, AI prompt, clarity, structure, system prompt, user prompt, few-shot, chain-of-thought, instruction tuning, prompt compression, token reduction, prompt rewrite, semantic preservation. Use when: improving unclear prompts, reducing token consumption,
npx skills add majiayu000/claude-skill-registry --skill prompt-enhancer-brixtonpham-claude-config --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Prompt Enhancer Skill ## Purpose Transform user prompts into enhanced, production-ready versions that are concise, clean, and optimally structured for AI agents and sub-agents. Includes optimization techniques for reducing LLM output token usage while maintaining semantic accuracy and backward compatibility. ## When to Use This Skill Use this skill when: - User explicitly asks to improve, enhance, or optimize a prompt - User sends an unclear, verbose, or poorly structured prompt - User mentions they want better results from AI interactions - User asks for help writing prompts for agents or automation - User's request lacks clarity or proper structure - User wants to reduce LLM output tokens or API costs - User needs to optimize JSON schema for token efficiency - User requests compact output format while maintaining compatibility ## Core Principles 1. **Conciseness**: Remove unnecessary words while preserving intent 2. **Structure**: Use clear formatting with multiple lines and logical sections 3. **XML Integration**: Mix natural text with XML tags for clarity and parsing 4. **Direct Mission**: Main task/quest/mission should NOT be wrapped in XML elements 5. **Clean Output**: Retu
- Purpose
- When to Use This Skill
- Core Principles
- Enhancement Process
- Input Analysis
- Task-Based Technique Selection (Optional)
- LLM Output Token Optimization
- Structural Improvements
- Language Optimization
- XML Tag Usage Guidelines
- Output Format
- Example Transformations
- Real-World Token Optimization Example
- Quality Checklist
What does the prompt-enhancer skill do?
Prompt engineering and optimization for AI/LLMs. Capabilities: transform unclear prompts, reduce token usage, improve structure, add constraints, optimize for specific models, backward-compatible rewrites. Actions: improve, enhance, optimize, refactor, compress prompts. Keywords: prompt engineering, prompt optimization, token efficiency, LLM prompt, AI prompt, clarity, structure, system prompt, user prompt, few-shot, chain-of-thought, instruction tuning, prompt compression, token reduction, prompt rewrite, semantic preservation. Use when: improving unclear prompts, reducing token consumption,
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill prompt-enhancer-brixtonpham-claude-config --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.