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Brand voice kit

Skill architshahdigital/claude-marketing-skills/skills/brand-voice-kit

Define a brand's voice and turn it into a reusable rule set that keeps every piece of AI-generated content on-brand. Use when the user is setting up a brand voice, wants consistency across writers/channels, needs a voice guide, or wants to "make this sound like us." Produces a voice profile (traits, do/don't, lexicon, examples) that can be pasted into any content prompt as guardrails. Triggers on: "brand voice", "tone of voice", "make it sound like us", "voice guide", "brand consistency", "style guide", "on-brand".From its SKILL.md

Install
npx -y skills add architshahdigital/claude-marketing-skills --skill brand-voice-kit

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SKILL.md

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Brand Voice Kit

A brand voice only works if it's operational β€” specific enough that a person or a model can apply it without guessing. This skill turns fuzzy adjectives ("professional but friendly") into a concrete rule set you can drop into any content workflow as guardrails.

Fallback: Running in Cloud/Web Environments (e.g., Claude.ai, CoWork)

If you are running in a cloud-based or web-based environment (such as Claude.ai web or CoWork) where local file system or repository access is unavailable:

  1. Ask the user to paste 2-3 examples of writing they like, 1-2 examples they dislike, and their target audience.
  2. Conduct the voice analysis and build the rule set manually in-context.
  3. Output the structured Voice Profile using the templates below.

Workflow

  1. Intake & Material Review:

    • Gather sample articles, emails, or posts.
    • Define target customer persona and context (e.g., B2B enterprise vs. consumer D2C).
  2. Establish Voice Traits (3–4 traits):

    • Define traits as clear spectrums (e.g., Formal to Casual). Specify where on the spectrum the brand sits.
  3. Define Do / Don't Rules:

    • Map exact language behaviors, not just adjectives. Specify what to write and what to avoid.
  4. Lexicon & Formatting Rules:

    • Document permitted terminology, banned buzzwords, emoji policies, and punctuation quirks.
  5. Provide Before / After Examples:

    • Provide 2–3 side-by-side examples showing a generic sentence rewritten to match the brand voice.

Templates & Output Format

Ensure the brand voice profile is generated in a clean, drop-in format:

1. Brand Voice Profile

🏷️ Voice Traits & Spectrums

  • Trait 1: [Name, e.g. Conversational] β€” Warm, personal, direct to consumer. Formal ―――—●― Casual
  • Trait 2: [Name, e.g. High Information] β€” Stat-driven, direct, educational. Speculative ―――——● High-Proof

πŸ“ Rules Matrix

DoDon't
Write short, active sentences.Corporate hedging (e.g., "we strive to").
Address the reader as "you" directly.Third-person distance (e.g., "users should").
Use concrete examples and exact stats.Buzzword stacking (e.g., "synergy", "disruptive").

πŸ“– Lexicon & Guidelines

  • Approved Terms: [term1], [term2], [term3]
  • Banned Buzzwords: [word1], [word2], [word3]
  • Emoji/Formatting Policy: E.g., Maximum 1 emoji per paragraph, no emojis in headers.

πŸ”„ Voice Refinement Examples

- [Generic: Our platform assists businesses in optimizing their social campaigns for enhanced user engagement.]
+ [On-Brand: We build tools that make your ads stand out so you get more clicks and sales.]

[!TIP] The One-Line North Star: Create a single, memorable sentence that sums up the voice (e.g., "Write like an experienced colleague explaining a concept over coffee.") so writers can quickly QA their drafts.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most marketing audience skills give in 751 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

  • gather sample materials and define target audience
  • define three to four voice traits as spectrums
  • map specific language behaviors as do and don't rules
  • document permitted terminology and banned buzzwords
  • specify emoji and punctuation policies
  • provide two to three before and after examples

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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