tone-shifter
SkillDev toolsRewrite 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'.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the tone-shifter skill
What this skill tells your AI
The instructions your AI receives, as published by mikefluff/skills in skills/tone-shifter/SKILL.md and read by ahel’s review.
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:
- add or remove substantive claims (use
writer/essay-write/prose-editto rewrite content); - generate viral hooks (use
viral-text); - check translation parity (use
translation-sync); - audit canon (use
canon-check).
ROLE
Read input + target register → output the same content rewritten in the target register → run the writer 4-layer cleanup so the result is shippable.
PIPELINE
-
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. -
Confirm target register. The user must name the target. If unclear, ask: "Which register? casual / friendly-professional / business-formal / academic / technical / plain-explainer."
-
Identify deltas. Look up
references/transformation-rules.mdfor the source→target pair and gather the specific changes: contractions on/off, sentence length, vocab swaps, hedge density, jargon level, person (1st / 2nd / 3rd). -
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.
-
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 — seewriter/SKILL.md. -
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.
MODES
tone-shifter <text> --to <register>— shift to named targettone-shifter <text> --to <register> --from <register>— explicit source (skips detection)tone-shifter <text> --to <register> --conservative— apply only safe deltas (vocab + contractions); skip restructuringtone-shifter <text> --analyze— return only the detected source register + suggested targets, do not rewritetone-shifter <text> --profile <profile.json>— apply a custom brand-voice JSON profile (vocabulary, avoidWords, hooks, ctaPhrases) on top of register shifttone-shifter --infer-profile <samples...>— read 2-5 sample texts and output a brand-voice JSON profile for reviewtone-shifter <text> --verify-profile <profile.json>— read-only check: does the passage match the profile? Returns structured report.
REFERENCES (load on demand)
| File | When to load |
|---|---|
| references/registers.md | When detecting source or naming target — defines the 6 registers and their detection markers |
| references/transformation-rules.md | After source+target known — the specific deltas to apply for each pair |
| 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 |
EXAMPLES
See examples/before-after.md for 4 calibration pairs covering the most-common shifts.
CONSTRAINTS
- Do not change facts. If the input says "we raised $4M in 2023", the output cannot say "we raised several million" or "we raised in the early 2020s".
- Do not change structure unless register demands it. Casual register may merge two short academic sentences into one. Academic register may split a casual run-on. But the order of points stays.
- Do not invent transitions. The transformation is local. If the input has rough transitions, they stay rough — the user can run
prose-editfor that. - Preserve quoted speech verbatim. Quoted material does not get tone-shifted; only narration around it.
- Person changes (1st → 3rd, you → reader) only if the target register strictly requires it. Otherwise preserve original person.
INVOCATION HINTS
When the user says any of:
- "make this more casual / formal / professional / friendly / academic / accessible"
- "rewrite for a younger / older audience"
- "turn this into [email / Slack / LinkedIn / blog / academic] tone"
- "less salesy", "less corporate", "less jargon", "less formal"
- "give me a plain-English version"
Use this skill. If the user wants a viral version (hook + CTA), use viral-text. If they want fiction voice, use prose-edit.
Signals
- GitHub stars
- 21
- Forks
- 1
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
tone-shifter- Source
- github.com/mikefluff/skills