skill-creator
Scaffold a new Claude Code skill with SKILL.md, frontmatter, and bundled resources. Use when creating a custom skill, standardizing skill structure across a team, or packaging a skill for distribution.
voice-refine
Transform verbose voice input into structured, token-efficient Claude prompts. Use when cleaning up voice memos, dictation output, or speech-to-text transcriptions that contain filler words, repetitions, and unstructured thoughts.
Full skill instructions
Transform verbose, stream-of-consciousness voice dictation into structured, token-efficient prompts for Claude Code.
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
## 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]
| 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) |
/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...
/voice-refine --direct --en
[voice input in any language → sends English prompt directly]
| Metric | Target |
|---|---|
| Token reduction | 60-70% |
| Information retention | >95% |
| Structure clarity | High |
Remove: filler words ("euh", "um", "like", "basically"), repetitions, tangents, hedging ("maybe", "probably" unless relevant), politeness padding ("please", "could you").
Preserve: technical requirements, constraints, existing code context, expected output format, edge cases, business logic rules.
guide/ai-ecosystem.md - Voice-to-Text Tools sectionexamples/before-after.md - Full transformation examplesScaffold a new Claude Code skill with SKILL.md, frontmatter, and bundled resources. Use when creating a custom skill, standardizing skill structure across a team, or packaging a skill for distribution.
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