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Get Started Free →Use when the user wants to define, document, or enforce how a brand sounds in writing. Trigger on 'brand voice', 'tone of voice', 'brand personality', 'voice guidelines', 'banned words', 'how the brand writes', 'style guide for copy', or 'copy does not sound like us'.
.claude/skills/minhnv0807-35-brand-voice-global/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-10 | ✗→✓ | ▲ Improved | 183% | 0% |
| case-01 | ✗→✓ | ▲ Improved | 42% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 416% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 91% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 174% | 0% |
The foundation skill of the content cluster. Every other content skill — 36-content-brief-global, 37-social-caption-global, 04-script-video-global, 05-ad-copy-global, 14-email-marketing-global, 38-community-seeding-global — reads this document before writing. Without it, output is technically correct and tonally inconsistent.
Read .agents/product-marketing-context-global.md and any existing brand guideline first. If information is missing, ask up to 4 questions:
09-customer-insight-global first so word choices are sourced, not invented.Pick exactly 3 core adjectives, each with one sentence explaining why it reflects the brand truthfully. More than 3 dilutes the voice.
Illustrative example (a DTC skincare brand):
Also record 3 things the brand must never be perceived as (for example: not luxury-aloof, not pressure-selling, not vague-wellness).
For each dimension write both columns. The "is not" column matters as much as the first — it is what stops voice drift.
| Dimension | The brand is... | The brand is not... | |-----------|-----------------|---------------------| | Energy | warm / measured / high-energy] | ...] | | Formality | casual / semi-professional / formal] | ...] | | Person and address | we-you / I-you / third person] | ...] | | Use of evidence | always a number / story first, data second] | ...] | | Handling objections | acknowledge then explain / rebut with proof] | ...] |
09-customer-insight-global)."game-changer", "revolutionary", "unlock your potential", "don't miss out", "act now", "hurry — limited time only", "take it to the next level", "elevate your noun]", "in today's fast-paced world", "we're excited to announce", "best-in-class", "world-class", "seamlessly", "one-stop shop", "must-have", "literally life-changing", "no-brainer", "synergy", "leverage" (as a verb in customer-facing copy).
Answer all 5:
Each example needs: an off-voice version, an on-voice version, and one line naming the difference. All 5 situations are mandatory, written for real — never left as placeholders. Writers use this section more than any other.
Illustrative set, same DTC skincare brand (Direct / Practical / Evidence-led):
1. Product launch caption
2. Replying to a negative comment
3. Promotion announcement
4. Educational post
5. Testimonial / case study
Core voice is unchanged. Only format, length, and register shift.
| Channel | Adjust vs. core | Keep constant | |---------|-----------------|---------------| | Facebook | Longer form allowed, conversational, light emoji if on-brand | Tone, vocabulary | | Instagram | Visual leads, first line carries the hook, tighter caption | Personality, banned words | | LinkedIn | One notch more professional, first-person point of view, no hard sell | Directness, evidence habit | | TikTok | 1-2 lines, spoken-word rhythm, keyword-forward for search | Core message | | X | Compressed to a single idea, no wind-up | Point of view, precision | | Email | Greeting and sign-off, slightly warmer, one clear ask | Directness, actionability |
File name: brand-voice-[brand]-[YYYYMMDD].md
markdown# Brand Voice Document — [Brand] ## I. Brand personality - [Adjective 1]: [one-sentence rationale] - [Adjective 2]: [one-sentence rationale] - [Adjective 3]: [one-sentence rationale] - Never perceived as: [3 things] ## II. Tone of voice | Dimension | The brand is... | The brand is not... | |-----------|-----------------|---------------------| | Energy | | | | Formality | | | | Person and address | | | | Use of evidence | | | | Handling objections | | | ## III. Vocabulary **Use often:** [words / phrases, with source where customer-derived] **Avoid:** [words / phrases] **Banned words:** [hard-stop list] **Canonical product names:** [agreed spelling per product/plan] ## IV. Sentence rules - Average sentence length: [short / mixed / long] — [why] - Rhetorical questions: [when yes / when no] - Bullets vs paragraphs: [ratio + context] - Opening pattern: [pain / curiosity / data / story] - Closing pattern: [CTA / question / summary] ## V. Before / after — 5 examples ### 1. Product launch caption - Before: "[off-voice]" - After: "[on-voice]" - Difference: [one line] ### 2. Replying to a negative comment [same format] ### 3. Promotion announcement [same format] ### 4. Educational post [same format] ### 5. Testimonial / case study [same format] ## VI. Platform adaptation | Channel | Adjust vs. core | Keep constant | |---------|-----------------|---------------| | | | | ## VII. Copy approval checklist - [ ] Read it aloud — does it sound like a person or like a report? - [ ] Any banned words present? - [ ] Does the first line earn the second? - [ ] Any word that can be cut without losing meaning? Cut it. - [ ] Is the next action obvious to the reader? - [ ] Is every claim substantiable if challenged? - [ ] Cover the logo — does it still read as us?
09-customer-insight-global: run first — real customer language from reviews and calls is the raw material for vocabulary.36-content-brief-global: every brief cites the tone and banned words from here.37-social-caption-global, 04-script-video-global, 05-ad-copy-global, 14-email-marketing-global: read this document before producing output.product-marketing-context-global: source of positioning, audience, and price point that the voice must fit.brand-voice-[brand]-[YYYYMMDD].md.| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-10 | fail→pass | 14,240 | 30,228 | +112% | 1 | 1 | 0% | 2,396 | 6,787 | +183% | 0 | 0 | — |
case-01 | fail→pass | 33,704 | 34,097 | +1% | 1 | 1 | 0% | 5,714 | 8,097 | +42% | 0 | 0 | — |
case-02 | fail→fail | 48,700 | 25,401 | -48% | 1 | 1 | 0% | 7,604 | 7,311 | -4% | 0 | 0 | — |
case-03 | fail→pass | 8,539 | 34,331 | +302% | 1 | 1 | 0% | 1,525 | 7,866 | +416% | 0 | 0 | — |
case-04 | pass→pass | 9,140 | 11,849 | +30% | 1 | 1 | 0% | 713 | 3,806 | +434% | 0 | 0 | — |
case-05 | pass→pass | 9,121 | 13,171 | +44% | 1 | 1 | 0% | 1,601 | 3,910 | +144% | 0 | 0 | — |
case-06 | pass→pass | 22,611 | 26,676 | +18% | 1 | 1 | 0% | 2,934 | 6,086 | +107% | 0 | 0 | — |
case-07 | fail→pass | 26,094 | 30,099 | +15% | 1 | 1 | 0% | 3,513 | 6,726 | +91% | 0 | 0 | — |
case-08 | fail→pass | 19,628 | 27,328 | +39% | 1 | 1 | 0% | 2,348 | 6,422 | +174% | 0 | 0 | — |
case-09 | pass→pass | 17,030 | 7,764 | -54% | 1 | 1 | 0% | 2,787 | 4,007 | +44% | 0 | 0 | — |
case-11 | fail→pass | 18,383 | 28,039 | +53% | 1 | 1 | 0% | 2,952 | 7,500 | +154% | 0 | 0 | — |
case-12 | fail→pass | 18,756 | 22,790 | +22% | 1 | 1 | 0% | 3,148 | 6,497 | +106% | 0 | 0 | — |
case-13 | fail→fail | 27,644 | 23,908 | -14% | 1 | 1 | 0% | 4,878 | 6,860 | +41% | 0 | 0 | — |
case-14 | fail→pass | 16,773 | 19,958 | +19% | 1 | 1 | 0% | 2,779 | 6,230 | +124% | 0 | 0 | — |
case-15 | fail→fail | 19,561 | 25,753 | +32% | 1 | 1 | 0% | 2,971 | 7,008 | +136% | 0 | 0 | — |
case-16 | fail→pass | 15,183 | 13,116 | -14% | 1 | 1 | 0% | 2,290 | 4,623 | +102% | 0 | 0 | — |
case-17 | pass→fail | 16,329 | 17,300 | +6% | 1 | 1 | 0% | 2,608 | 5,546 | +113% | 0 | 0 | — |
case-18 | pass→pass | 13,313 | 26,144 | +96% | 1 | 1 | 0% | 2,261 | 6,883 | +204% | 0 | 0 | — |
case-19 | pass→pass | 14,220 | 16,445 | +16% | 1 | 1 | 0% | 2,390 | 5,217 | +118% | 0 | 0 | — |
case-20 | pass→pass | 19,863 | 15,438 | -22% | 1 | 1 | 0% | 3,352 | 5,084 | +52% | 0 | 0 | — |
case-21 | fail→pass | 13,198 | 17,325 | +31% | 1 | 1 | 0% | 2,281 | 5,507 | +141% | 0 | 0 | — |
case-22 | pass→pass | 16,821 | 28,233 | +68% | 1 | 1 | 0% | 2,807 | 7,662 | +173% | 0 | 0 | — |
case-23 | pass→pass | 18,677 | 22,823 | +22% | 1 | 1 | 0% | 3,154 | 6,209 | +97% | 0 | 0 | — |
case-24 | fail→pass | 17,138 | 16,457 | -4% | 1 | 1 | 0% | 2,652 | 5,346 | +102% | 0 | 0 | — |
case-25 | fail→pass | 17,150 | 14,608 | -15% | 1 | 1 | 0% | 3,014 | 5,102 | +69% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 25 cases were attempted. The headline lift of +44 percentage points is the difference between those two pass rates over the 25 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.