refine-prompts
Refine vague or unclear prompts into precise, actionable instructions. Use when user asks to clarify or improve instructions or when input is vague. Includes L1/L2/L3/L4 methodology, context enrichment, and intent clarification. Not for already clear prompts, simple questions, or when user explicitly rejects refinement.
Profile →npx skills add majiayu000/claude-skill-registry --skill refine-prompts-git-fg-meta-plugin-manager-2 --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.
<mission_control> <objective>Refine vague or unclear prompts into precise, actionable instructions using L1/L2/L3/L4 methodology.</objective> <success_criteria>Prompt refined to appropriate L-level with sufficient context and clear intent</success_criteria> </mission_control> ## The Path to High-Quality Prompts ### 1. Match Complexity to Structure Prompt structure should reflect task complexity. Simple tasks with complex templates waste tokens; complex tasks with simple prompts miss requirements. **Select L-level by purpose:** - **L1 (Single-sentence)**: Quick clarifications, straightforward outcomes - **L2 (Context-rich paragraph)**: Default choice—balances clarity and efficiency - **L3 (Structured bullets)**: Complex tasks with multiple constraints - **L4 (Template/framework)**: Reusable patterns, repeatable workflows **Why this works:** Right-sized structure ensures Claude understands requirements without over-constraining creativity or under-specifying deliverables. ### 2. Enrich Context, Reduce Ambiguity Add relevant background, technical constraints, and success criteria. Context prevents wrong assumptions and reduces clarification rounds. **Essential context elements:** - Te
- The Path to High-Quality Prompts
- 1. Match Complexity to Structure
- 2. Enrich Context, Reduce Ambiguity
- 3. Preserve What Matters, Delete What Doesn't
- 4. Specify Outputs Precisely
- Operational Patterns
- Core Methodology
- Execution Process
- STEP 1: Parse Input
- STEP 2: Apply Refinement
- STEP 3: Structure Output
- STEP 4: Deliver
- Validation Checklist
- Best Practices Summary
What does the refine-prompts skill do?
Refine vague or unclear prompts into precise, actionable instructions. Use when user asks to clarify or improve instructions or when input is vague. Includes L1/L2/L3/L4 methodology, context enrichment, and intent clarification. Not for already clear prompts, simple questions, or when user explicitly rejects refinement.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill refine-prompts-git-fg-meta-plugin-manager-2 --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.