prompt-polisher
Use when receiving messy, unstructured input like voice transcriptions, stream-of-consciousness notes, or rough document content that needs to be transformed into a polished, optimized prompt. Cleans up filler words, extracts intent, asks clarifying questions, applies Claude 4.x/Opus 4.5/Sonnet 4.5 best practices, and previews the polished prompt for approval before execution. Trigger phrases include "polish this", "clean this up", "turn this into a prompt", or when input is clearly rough/unstructured.
Best use case
prompt-polisher is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when receiving messy, unstructured input like voice transcriptions, stream-of-consciousness notes, or rough document content that needs to be transformed into a polished, optimized prompt. Cleans up filler words, extracts intent, asks clarifying questions, applies Claude 4.x/Opus 4.5/Sonnet 4.5 best practices, and previews the polished prompt for approval before execution. Trigger phrases include "polish this", "clean this up", "turn this into a prompt", or when input is clearly rough/unstructured.
Teams using prompt-polisher should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/prompt-polisher/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How prompt-polisher Compares
| Feature / Agent | prompt-polisher | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when receiving messy, unstructured input like voice transcriptions, stream-of-consciousness notes, or rough document content that needs to be transformed into a polished, optimized prompt. Cleans up filler words, extracts intent, asks clarifying questions, applies Claude 4.x/Opus 4.5/Sonnet 4.5 best practices, and previews the polished prompt for approval before execution. Trigger phrases include "polish this", "clean this up", "turn this into a prompt", or when input is clearly rough/unstructured.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Prompt Polisher
Transform messy, unstructured input into polished, Claude-optimized prompts using Anthropic's best practices.
## When to Activate
Activate this skill when:
- User provides voice transcription content (contains filler words, self-corrections, casual speech)
- User dumps stream-of-consciousness notes
- User pastes rough document content that needs structuring
- User explicitly asks to "polish", "clean up", or "turn this into a prompt"
- Input is clearly unstructured and intended as task instructions
## Workflow
Execute these stages in order:
### Stage 1: Voice Cleanup
If the input appears to be voice transcription or casual speech, clean it up:
**Remove:**
- Filler words: "um", "uh", "like", "you know", "basically", "actually", "literally", "right?"
- Self-corrections: "no wait", "I mean", "actually scratch that", "let me rephrase"
- False starts: repeated or abandoned sentence beginnings
- Verbal tics: "okay so", "let me think", "hmm"
**Normalize:**
- Convert spoken patterns to written form
- Fix run-on sentences
- Add proper punctuation
### Stage 2: Intent Extraction
Parse the cleaned input to identify:
| Element | What to Find |
|---------|--------------|
| Core task | What does the user actually want done? |
| Referenced files | Documents, project files, URLs mentioned |
| Constraints | Limitations, requirements, boundaries |
| Preferences | Style, format, approach preferences |
| Success criteria | What does "done" look like? |
| Scope | Single task vs. multi-step project |
### Stage 3: Gap Detection
Scan for missing or ambiguous elements:
- [ ] Ambiguous requirements ("process them somehow")
- [ ] Missing success criteria (no clear definition of "done")
- [ ] Unclear scope (single task or multi-step?)
- [ ] Format unspecified (code? prose? structured output?)
- [ ] Model unknown (Opus 4.5 or Sonnet 4.5?)
- [ ] Technical choices undefined (which library/approach/pattern?)
**If gaps exist, ask ALL clarifying questions at once:**
```
Before I polish this prompt, I need to clarify a few things:
1. [First gap-specific question]
2. [Second gap-specific question]
3. Which Claude model are you using? (Opus 4.5 / Sonnet 4.5 / Not sure)
```
Wait for user response before proceeding.
### Stage 4: Apply Best Practices
Reference [reference.md](reference.md) for detailed guidelines. Apply these transformations:
**Universal (Claude 4.x):**
- Make instructions explicit and direct (no hints)
- Add contextual framing (explain WHY, not just WHAT)
- Use positive framing ("use prose" not "don't use bullets")
- Structure with XML tags for complex inputs
- Use action-oriented language ("Change this" not "Can you suggest")
- Include chain of thought prompts for complex reasoning
- Define clear success criteria
- Use normal tone (avoid aggressive CAPS/MUST/CRITICAL)
**If Opus 4.5:**
- Add anti-over-engineering guardrail: "Keep solutions simple. Only make changes directly requested."
- Avoid the word "think" → use "consider", "evaluate", "believe"
- Leverage planning strength: "Build an editable plan before executing"
- Keep prompts token-efficient (don't over-pad)
- Provide policy/constraint context when relevant
**If Sonnet 4.5:**
- Break complex tasks into explicit steps
- Optimize for speed/throughput
- Add more explicit step-by-step guidance for intricate tasks
### Stage 5: Structure the Prompt
Generate the polished prompt using this template:
```xml
<context>
[Background info, relevant project context, referenced files, WHY this task matters]
</context>
<task>
[Clear, explicit statement of what needs to be done - action-oriented]
</task>
<requirements>
[Specific constraints, boundaries, must-haves, technical choices]
</requirements>
<success_criteria>
[What "done" looks like, how to verify completion]
</success_criteria>
<approach> <!-- Optional: include for complex tasks -->
[Suggested approach OR "Build an editable plan before executing"]
</approach>
```
**Formatting rules:**
- Keep each section focused and concise
- Use bullet points only when listing multiple items
- Omit sections that aren't relevant to the task
- For simple tasks, a streamlined version without XML tags is acceptable
### Stage 6: Preview for Approval
Present the polished prompt to the user:
```
Here's your polished prompt:
---
[POLISHED PROMPT CONTENT]
---
**Options:**
- **Execute** - Run this prompt now
- **Edit** - I'll modify something first
- **Redo** - Start over with different clarifications
```
**Wait for user approval before executing.**
### Stage 7: Execute or Iterate
Based on user choice:
- **Execute**: Immediately act on the polished prompt as if the user had typed it directly
- **Edit**: User modifies the prompt, then re-preview
- **Redo**: Return to Stage 1 with new input or Stage 3 for new clarifications
## Important Notes
- Always preview before executing - never skip the approval step
- If the input is already well-structured, acknowledge this and offer minor polish only
- Learn from user feedback - if they frequently edit a certain way, note the pattern
- For very short/simple inputs, use a streamlined format without full XML structure
- The goal is USEFUL prompts, not LONG prompts - be concise
## See Also
- [reference.md](reference.md) - Detailed Anthropic best practices for Claude 4.x, Opus 4.5, and Sonnet 4.5
- [examples.md](examples.md) - Before/after transformation examplesRelated Skills
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