audio-mix-maker
Mix music/audio onto an existing video via ffmpeg. Modes: replace, overlay, duck (sidechain compressor lowers music under speech). Volume + fade controls. Pure…
Rewrite text in a different register without changing meaning — formal↔casual, business↔academic, technical↔friendly, plain-explainer. 6 named registers + transformation deltas. Wraps `writer`. Use when the user says 'make this more casual / formal / accessible / business-like',
$ npx -y skills add Mikefluff/skills --skill tone-shifter --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/tone-shifterContext preview
The summary Claude sees to decide when to auto-load this skill.
Rewrite text in a different register without changing meaning — formal↔casual, business↔academic, technical↔friendly, plain-explainer. 6 named registers + transformation deltas. Wraps `writer`. Use when the user says 'make this more casual / formal / accessible / business-like',
name: tone-shifter description: "Rewrite text in a different register without changing meaning — formal↔casual, business↔academic, technical↔friendly, plain-explainer. 6 named registers + transformation deltas. Wraps `writer`. Use when the user says 'make this more casual / formal / accessible / business-like', 'rewrite for younger audience'." license: MIT allowed-tools: - Read - Write - Edit - Bash - Grep - Glob
<objective> Tone-shift a passage from one register to another while preserving the underlying claims, facts, structure, and information density. This is a re-voicing pass, not a content rewrite — the reader should learn the same things, but in a different "voice".
Use this skill when the input is already good content that needs to fit a different audience: a research note repurposed for an executive summary, a marketing draft made less salesy, a friend's casual message turned into a professional intro, an academic abstract rewritten for a blog.
This skill does NOT:
</objective>
Read input + target register → output the same content rewritten in the target register → run the `writer` 4-layer cleanup so the result is shippable.
1. **Detect source register.** Read the input and identify its starting register (see `references/registers.md`). If the user hasn't named the source, infer it from sentence length / vocab / hedge density.
2. **Confirm target register.** The user must name the target. If unclear, ask: "Which register? casual / friendly-professional / business-formal / academic / technical / plain-explainer."
3. **Identify deltas.** Look up `references/transformation-rules.md` for the source→target pair and gather the specific changes: contractions on/off, sentence length, vocab swaps, hedge density, jargon level, person (1st / 2nd / 3rd).
4. **Apply transformations clause-by-clause.** Don't paraphrase the whole text in one shot — that loses content. Walk through each sentence and apply only the deltas that fit. Preserve original sentence boundaries when possible.
5. **Pass through `writer`.** Final 4-layer clean: typography, anti-slop regex categories, structural-prose, ru-calques. This is the same final pass every other wrapper runs — see `writer/SKILL.md`.
6. **Diff-report.** Show before/after side-by-side with a 1-line note on which deltas were applied. The user reviews; they can ask for a different register or a partial revert.
| File | When to load | |---|---| | [references/registers.md](references/registers.md) | When detecting source or naming target — defines the 6 registers and their detection markers | | [references/transformation-rules.md](references/transformation-rules.md) | After source+target known — the specific deltas to apply for each pair | | [references/brand-voice-profile.md](references/brand-voice-profile.md) | When user provides a custom brand-voice profile (JSON), or asks for one to be inferred from samples — overlays registers with concrete vocabulary / banned words / hooks / CTAs |
See [examples/before-after.md](examples/before-after.md) for 4 calibration pairs covering the most-common shifts.
When the user says any of:
Use this skill. If the user wants a viral version (hook + CTA), use `viral-text`. If they want fiction voice, use `prose-edit`.
44 skills for Claude Code that make content — and refuse to let it read like a machine made it. Prose editing that strips the tells. Prompt engineering for 40+ image, video and music models, with optional one-command execution against the real APIs.
Repo: Mikefluff/skills
Mix music/audio onto an existing video via ffmpeg. Modes: replace, overlay, duck (sidechain compressor lowers music under speech). Volume + fade controls. Pure…
Turn a user photo into N profile-pic / headshot / avatar variants in a consistent style. Identity-preserve focused, defaults to nano-banana-pro. Multi-aspect…
Banner-ad / display-creative generator with standard-size presets: Google Display (leaderboard, medium rectangle, mobile, skyscraper), LinkedIn, OG image,…
Background removal utility — image in, transparent PNG out. Wraps Replicate-hosted models (851-labs/background-remover default; alternatives via…
Read-only story-bible auditor for fiction series with a documented canon. Cross-references character / artifact / location mentions in chapters against the…
Turn a topic or research brief into an N-slide Instagram / LinkedIn / TikTok carousel with consistent visual style and ready-to-post captions. Modes: --topic /…