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Brand voice

Skill 0xelitesystem/claude-skills-templates/skills/brand-voice

Apply a configured brand voice and tone guide to drafts, rewrites, and edits. Use whenever the user wants text edited to match their team's voice, asks for tone adjustments, or wants drafts brought into compliance with a style guide. Triggers on "rewrite in our voice", "apply our tone", "edit this draft", "make this sound like us", "fix the voice", or any rewrite request where consistency with a brand style is the goal. Always read references/brand-voice.md before making edits, and use this skill rather than free-form rewriting when style consistency matters.From its SKILL.md

Install
npx -y skills add 0xelitesystem/claude-skills-templates --skill brand-voice

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

2.6 KB, 483 tokens by cl100k_base, as published. Nobody here has run it

Brand Voice

Applies a configured voice and tone guide to drafts. The voice itself lives in references/brand-voice.md so it can be customized without touching the skill logic.

Workflow

  1. Read references/brand-voice.md in full before editing anything.
  2. Identify the input: a draft pasted by the user, an uploaded file, or a section of an existing document.
  3. Run the rewrite pass below.
  4. Output the rewritten version, then a short audit of what changed.

Rewrite pass

For each paragraph in the input:

  • Check it against the voice attributes in the reference file.
  • Check it against the banned-words list.
  • Check it against the preferred-phrasings list.
  • Rewrite if any check fails. Leave alone if all pass.
  • Preserve the original meaning and key facts. Only change how it is said.

What to preserve

  • Numbers, dates, names, quotes (exact)
  • Section structure (headings, ordering, list items)
  • Technical accuracy (do not soften precise language into vague language)
  • Length within plus or minus 15% unless the user asked for shorter or longer

What to change

  • Word choice that violates the banned-words list
  • Sentence rhythm that conflicts with the stated voice (e.g., long flowing prose when the voice is "punchy")
  • Formality level (casual versus formal)
  • Filler and hedging that is not in the voice
  • Default-AI patterns that creep in (em-dashes, "not just X but Y", tricolon abuse)

Output format

Render in two parts:

## Rewritten

<the full rewritten text>

## Changes

- <one-line summary of the most important change>
- <next change>
- (up to 5 total)

When the reference file is missing or empty

If references/brand-voice.md is missing, or contains only the placeholder template with no user content, do not guess at the voice. Tell the user the reference file needs content first, and offer to interview them with three specific questions:

  1. What three adjectives describe your voice? (e.g., direct, warm, technical)
  2. What words or phrases do you ban?
  3. Paste two sentences in your voice and two that fail.

What ships with it: 1 file

1.4 KB alongside SKILL.md

references/

Gives 0 of the 12 instructions most marketing audience skills give in 483 tokens

Counted across 690 of the 894 authors here whose files we hold, read 2026-08-07

  • Apply Poppins font to headingsin 41 of 690, across 6 files
  • Apply Lora font to body textin 41 of 690, across 6 files
  • Use Arial fallback for headingsin 39 of 690, across 4 files
  • Use Georgia fallback for body textin 39 of 690, across 4 files
  • Maintain text hierarchy and formattingin 39 of 690, across 4 files
  • Use accent colors for non-text shapesin 38 of 690, across 3 files
  • Use RGB values for precise color matchingin 38 of 690, across 3 files
  • Use brand colors for primary text and backgroundsin 36 of 690, across 1 file
  • Read product marketing context file before asking questions, starting, or auditingin 35 of 690, across 23 files
  • Use active voice instead of passive voicein 26 of 690, across 10 files
  • Implement or generate appropriate JSON-LD structured datain 24 of 690, across 17 files
  • Prioritize clarity over clevernessin 22 of 690, across 8 files

Said here and by no other author read

  • Identify the input source before rewriting
  • Check each paragraph against voice attributes
  • Check each paragraph against preferred phrasings
  • Leave passing paragraphs unchanged
  • Preserve original meaning and key facts
  • Preserve exact numbers, dates, names, and quotes

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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