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esmefongesmefong/gtm-skills/brand-voice-guide/SKILL.md

brand-voice-guide

Skill0 starsChanged 3 months agoMITView on GitHub

Extract a brand's voice from its real writing and build a structured voice directory a team (or an AI agent) can write from consistently. Harvests existing content — homepage, blog, posts, emails, changelog — into voice-core rules, per-channel guidance, and a writing standard whose Avoid section names the banned words and voice-killing patterns, each grounded in verbatim samples. Interviews the user only to fill what the samples can't answer. Use whenever the user says "brand voice", "voice guide", "tone of voice", "voice and tone", "brand voice guide", "define our voice", "extract our voice", "style guide", "voice standard", or wants to document how their brand sounds so content stays on-brand at scale. Works across industries and channels. Builds the guide; it does not police drafts — that is the job of a separate content-quality-check skill.

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The file

We split this skill into the rules it gives an agent

2 rules. 0 are common, 0 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Run the extraction passes in references/extraction-passes.md.

    line 70
  2. Very specific:

    Avoid section of writing-standard.md are what it checks drafts against.

    line 155

“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Brand Voice Guide

Extract how a brand actually sounds from what it has actually written, and turn it into a directory that a copywriter, a new hire, or a Claude agent can produce on-brand content from. One conviction drives it: a voice guide is extracted from real writing, not invented from adjectives. "We're bold, human, and authentic" describes nothing. A verbatim line the brand wrote, and a rule named from it, describes everything.

The output is a directory of reference files (not a single essay), so it can be consulted modularly at the moment of writing — the voice-core rules always, the relevant channel file for the piece at hand. It mirrors the structure a production content system consults before generating a word.

What this builds (and what it doesn't)

  • It builds the voice directory: voice-core.md (the character), writing-standard.md (the concrete rules — a Do half and a severity-tagged Avoid half), per-channel files, real-examples.md, plus light about-company.md / icp.md context.
  • It does not check drafts. Governing new content against the guide (AI tells, template language, brand-rule violations) is the job of a separate content-quality-check skill. This skill produces the standard that skill enforces — the Avoid section of writing-standard.md is the part it reads.

Inputs (harvest first, ask only for the gaps)

The skill is harvest-first: it extracts as much as possible from existing writing before asking the user anything. Collect what exists; note what's missing.

InputWhy it mattersIf missing
Brand / product one-linerAnchors what "on-brand" meansAsk; don't proceed without it
Writing samples (the harvest)The evidence base — voice is extracted from theseInterview mode (see Phase 3)
Active channels + which are intentionalDetermines which channel files to buildAsk; build files only for intentional channels
Existing ICP / audienceVoice is aimed at a readerIf icp-research was run, drop its output in as icp.md; else gather lightly
A published piece the brand is proud ofThe clearest signal of the "real" voiceAsk the user to name one

The single most useful ask: "Point me at the two or three things you've published that felt most like you — and one thing in your space that makes you cringe." The contrast defines the voice.

The workflow

Five phases. Harvest builds the draft; the interview only fills gaps; the Avoid rules come last. Show the user the tagged samples (end of Phase 2) and the draft files (Phase 4) before finalizing.

Phase 1 — Scope and intake

  1. Confirm the brand one-liner and who the writing is for (reader/ICP).
  2. List every channel the brand publishes on, and mark each intentional (a real voice, published with purpose) vs. passive (occasional, cross-posted without thought). Build channel files only for intentional ones. A brand whose Discord is its community needs voice-discord.md more than a twice-a-year Instagram needs voice-instagram.md.
  3. Inventory the writing samples on hand; if there's little to no published content, switch to interview mode (Phase 3 does the discovery instead of the harvest).

Phase 2 — Harvest (extract voice from the samples)

Run the extraction passes in references/extraction-passes.md. In short: read everything and pull, verbatim, the language that could only come from this brand. Do not paraphrase — the specificity is the value. Capture:

  • How they describe what they do (exact phrases), and any stated belief that could start an argument.
  • The voice patterns that repeat: how pieces open, how they close, sentence length and rhythm, the relationship to the reader (explain / challenge / accompany), where the writing is most alive vs. most performed.
  • Channel differences: how the register shifts between, say, email and LinkedIn.
  • Recurring mechanics: preferred verbs and nouns, banned words, capitalization and number habits.

Output of this phase: a tagged bank of verbatim lines, grouped by the file each will feed. Show it.

Phase 3 — Interview to fill gaps (only what samples can't answer)

Some things rarely appear in polished content. Ask targeted questions from references/question-bank.md only where the harvest came up empty. The highest-value ones:

  • The contrarian belief. "What does the brand believe that most competitors won't say out loud — the thing you'd say at dinner that might start an argument?"
  • The relationship decision. "If the brand were a person at a dinner table, what role does it play?" Offer contrast pairs when they stall (mentor vs. peer; simplify vs. sit-in-complexity; projects-confidence vs. owns-the-uncertainty; challenges the reader vs. meets them where they are). The defense of the choice is more useful than the choice.
  • Who it's NOT for, and what the brand would never say even if it worked for others.
  • The one-sentence summary. "Write the sentence you'd want someone to say about the brand after three months of your content," then push once: "which word in that isn't quite true?"

In interview mode (no content to harvest), Phase 3 carries the whole discovery: work the question bank front to back, and lean on the AI-draft-reaction technique below to surface anti-patterns.

Phase 4 — Build the directory

Assemble each file using references/output-templates.md. Non-negotiable rules:

  • Every file contains at least one real, verbatim sample the brand produced. A voice file with no real language is a horoscope. If you can't ground a file, it's a gap, not a guess.
  • Every tonal pillar gets a named rule plus a verbatim do (and ideally a don't).
  • Use the brand's exact words for rules ("we never sound like a professor who needs to impress you" goes in verbatim, not softened to "avoids academic tone").
  • Build channel files one at a time; when a brand has 4+ channels, do the 2-3 highest-frequency ones first and add the rest in a second pass rather than producing shallow files for all of them.

Phase 5 — The Avoid rules (last) and verification

Build the Avoid section of writing-standard.md last, because an "avoid" only has meaning against a defined voice. It's the single home for banned words and voice-killing patterns (there is no separate anti-patterns file). Build it from three sources (detail in references/output-templates.md):

  1. A universal starter list of generic/AI tells, which the user confirms or overrides.
  2. The AI-draft-reaction: generate a short, styleless AI draft on one of the brand's own topics and have the user mark every line that makes them wince. These brand-specific tells are the most valuable ones and appear on no universal list.
  3. The one industry phrase the brand refuses to use.

Tag each entry with severity (HIGH/MEDIUM/LOW) so the future content-quality-check skill can act on it. Then verify: read back the key decisions ("here's who you told me you are / who you're for / how you show up / what you never do — anything that doesn't sound exactly like you?"), and run the distinctiveness test on every voice file: if a line could be lifted onto a competitor's site unchanged, it isn't voice — rewrite or cut it. Close with a Gaps note (what's assumed vs. grounded).

Output

A directory, built with references/output-templates.md:

brand-voice/
├── about-company.md          # what it does, why it exists, the contrarian belief
├── icp.md                    # who it writes for (drop in icp-research output if you have it)
├── voice-core.md             # the character: tonal pillars (each with a verbatim sample), sentence
│                             #   rules, "persona we are NOT", the distinctiveness test
├── writing-standard.md       # the concrete rules — Do (words to use, formatting, caps, numbers) and
│                             #   Avoid (banned words + voice-killing patterns, severity-tagged; built last)
├── voice-<channel>.md        # one per INTENTIONAL channel: structure, hook patterns used/avoided,
│                             #   length targets, formatting
└── real-examples.md          # a small library of in-voice lines to reference for shape

Channel files are added only for channels the brand actively and intentionally publishes on. There is one home for "don't": the Avoid section of writing-standard.md (no separate anti-patterns file).

Composes with other skills

  • icp-research — if it's been run, use its output as icp.md instead of re-gathering. Cross-link.
  • content-quality-check — the enforcement side. This skill's voice-core.md and the Avoid section of writing-standard.md are what it checks drafts against.

Failure modes to avoid (the quality bar)

  • Adjective soup — "bold, human, authentic." Describes nothing. Every rule needs a verbatim sample.
  • Describing instead of extracting — writing what the voice should be rather than naming what it already is in the samples.
  • Horoscope files — a voice file with no real brand language in it.
  • Generic that survives the swap — a line that could sit on a competitor's site unchanged. Rewrite.
  • Avoid rules written first — they're meaningless before the voice is defined; build them last.
  • A file per dead channel — build only for channels published with intent.
  • Paraphrasing the user's exact words — the specificity is the whole value; keep it verbatim.

Bundled references

  • references/extraction-passes.md — the harvest engine: what to collect, and the passes that draft each file. Read at Phase 2.
  • references/question-bank.md — the gap-filling questions, mapped to each file. Read at Phase 3.
  • references/output-templates.md — the exact shape of every file, plus the universal Avoid starter list. Read at Phase 4/5.
  • examples/ — worked examples built from real public copy. Each is a company folder holding the harvest (input.md) and the full multi-file voice directory the skill produced (brand-voice/): examples/cohere/ (primary; enterprise-sovereign, ownership-framed) and examples/notion/ (secondary; warm, playful-clear). Different voices, so the contrast shows the skill capturing what's actually distinctive.

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