Voice Refine Skill
Transform verbose, stream-of-consciousness voice dictation into structured,
token-efficient prompts for Claude Code.
When to Use
- Input from voice dictation (Wispr Flow, Superwhisper, macOS Dictation)
- Verbose text >150 words
- Contains filler words, repetitions, or tangents
- Natural speech patterns that need structure
Transformation Pipeline
1. DEDUPE → Remove repetitions and filler words
2. EXTRACT → Identify core requirements and constraints
3. STRUCTURE → Organize into standard sections
4. COMPRESS → Reduce to ~30% of original while preserving intent
Output Format
## Contexte
[Project context, existing stack, relevant files]
## Objectif
[Single sentence: what needs to be built/changed]
## Contraintes
- [Constraint 1]
- [Constraint 2]
- [etc.]
## Output attendu
[Expected deliverables: files, format, tests]
Flags
| Flag |
Effect |
--confirm |
Show refined prompt before sending to Claude (default) |
--direct |
Send refined prompt directly without confirmation |
--verbose |
Keep more detail, less compression |
--en |
Output in English (default: matches input language) |
Usage Examples
Basic Usage
/voice-refine
Alors euh j'aimerais que tu m'aides à faire un truc, en fait j'ai une API
qui renvoie des données utilisateurs et je voudrais les afficher dans un
tableau React, mais attention il faut que ça soit paginé parce que y'a
beaucoup de données, genre des milliers d'utilisateurs, et aussi faudrait
pouvoir trier par nom ou par date d'inscription, ah et on utilise Tailwind
dans le projet donc faut que ça matche avec ça...
With Flags
/voice-refine --direct --en
[voice input in any language → sends English prompt directly]
Compression Metrics
| Metric |
Target |
| Token reduction |
60-70% |
| Information retention |
>95% |
| Structure clarity |
High |
Integration with Voice Tools
Wispr Flow
- Dictate with
Cmd+Shift+Space
- Paste into Claude Code
- Run
/voice-refine
Superwhisper
- Record with hotkey
- Text appears in active window
- Run
/voice-refine to structure
macOS Dictation
Fn Fn to start- Speak naturally
- Run
/voice-refine to clean up
What Gets Removed
- Filler words: "euh", "um", "like", "you know", "basically"
- Repetitions: same concept stated multiple ways
- Tangents: off-topic thoughts
- Hedging: "maybe", "I think", "probably" (unless relevant)
- Politeness padding: "please", "could you", "I'd like"
What Gets Preserved
- Technical requirements
- Constraints and limitations
- Context about existing code
- Expected output format
- Edge cases mentioned
- Business logic rules
See Also
guide/ai-ecosystem.md - Voice-to-Text Tools sectionexamples/before-after.md - Full transformation examples
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