--- name: brand-voice-extraction description: | Systematic methodology for capturing a client's authentic brand voice from writing samples, existing content, questionnaire responses, and stakeholder preferences. USE THIS SKILL WHEN: - Analyzing writing samples to document voice - Creating voice guidelines for a new client - Auditing existing content for voice consistency - User mentions "brand voice", "tone", "writing style", "voice extraction" - Preparing to write copy that needs to match client's voice - Building voice profile as part of client discovery OUTPUTS: Brand Voice Profile JSON with evidence-backed attributes allowed-tools: Read, Grep, Glob --- # Brand Voice Extraction Skill ## Overview Brand voice is the consistent personality expressed through words. This skill provides a rigorous, evidence-based methodology for extracting voice attributes from client materials—not inventing them, not assuming them, but documenting what's actually there. ## The Voice Extraction Framework ### The Six Core Voice Dimensions Every brand voice can be mapped across six dimensions. Each is a spectrum, not a binary: ``` DIMENSION 1: FORMALITY ├─ 1-2: Very Casual ("Hey! Let's chat about...") ├─ 3-4: Casual ("Here's the deal...") ├─ 5-6: Balanced ("We're happy to help you...") ├─ 7-8: Professional ("We are pleased to assist...") └─ 9-10: Very Formal ("It is our privilege to serve...") DIMENSION 2: ENTHUSIASM ├─ 1-2: Reserved ("The product works well.") ├─ 3-4: Measured ("We're confident you'll see results.") ├─ 5-6: Engaged ("We love helping clients succeed!") ├─ 7-8: Energetic ("This is AMAZING and you'll love it!") └─ 9-10: Exuberant ("OMG this will literally change your LIFE!!!") DIMENSION 3: HUMOR ├─ 1-2: Serious (No humor, all business) ├─ 3-4: Occasional wit (Light touches, subtle) ├─ 5-6: Playful (Regular humor, approachable) ├─ 7-8: Witty (Clever wordplay, personality-forward) └─ 9-10: Comedy-forward (Humor is the brand) DIMENSION 4: DIRECTNESS ├─ 1-2: Soft/Indirect ("You might consider...") ├─ 3-4: Gentle ("We suggest...") ├─ 5-6: Clear ("Here's what to do...") ├─ 7-8: Direct ("Do this.") └─ 9-10: Bold/Blunt ("Stop wasting time. Do this now.") DIMENSION 5: TECHNICAL COMPLEXITY ├─ 1-2: Very Simple (5th grade reading level) ├─ 3-4: Accessible (8th grade, no jargon) ├─ 5-6: Moderate (Some industry terms, explained) ├─ 7-8: Technical (Industry jargon expected) └─ 9-10: Expert (Dense, specialized vocabulary) DIMENSION 6: WARMTH ├─ 1-2: Distant/Impersonal ("Users will find...") ├─ 3-4: Neutral ("You can...") ├─ 5-6: Friendly ("We're here for you...") ├─ 7-8: Warm ("We genuinely care about...") └─ 9-10: Intimate ("You're part of our family...") ``` --- ## Extraction Process ### Step 1: Gather Writing Samples **Ideal Sample Set:** - 3-5 pieces of existing content (website, emails, social) - Stakeholder writing samples (founder emails, team communications) - Content they admire (competitors or brands they like) - Content they dislike (what to avoid) **Minimum Viable:** - At least 1 substantial piece (500+ words) - OR questionnaire responses about voice preferences **Document Your Inputs:** ```json { "samples_analyzed": [ { "source": "Homepage copy", "word_count": 450, "content_type": "marketing", "url_or_location": "https://..." } ] } ``` ### Step 2: Analyze Each Sample For each writing sample, extract: #### A. Sentence-Level Patterns ```markdown SENTENCE LENGTH: - Average words per sentence: [count] - Range: [shortest] to [longest] - Pattern: [short/medium/long/varied] SENTENCE STRUCTURE: - Simple sentences: [%] - Compound sentences: [%] - Complex sentences: [%] - Questions used: [yes/no, frequency] - Exclamations used: [yes/no, frequency] EXAMPLES: - Typical sentence: "[quote]" - Atypical sentence: "[quote]" ``` #### B. Word-Level Patterns ```markdown VOCABULARY: - Preferred verbs: [list with examples] - Avoided verbs: [list or note absence] - Industry jargon used: [yes/no, examples] - Contractions: [always/sometimes/never] SPECIFIC WORD CHOICES: - How do they say "you"? [you/y'all/folks/clients/customers] - How do they say "we"? [we/our team/the company/I] - Power words used: [list] - Words conspicuously absent: [list] EXAMPLES: - Characteristic phrase: "[quote]" - Repeated pattern: "[quote]" ``` #### C. Emotional Tone ```markdown EMOTIONAL REGISTER: - Primary emotion conveyed: [confidence/excitement/calm/urgency/etc.] - Secondary emotions: [list] - Emotions avoided: [list] EVIDENCE: - Quote showing primary emotion: "[quote]" - Quote showing avoidance: "[quote]" ``` #### D. Structural Patterns ```markdown PARAGRAPH LENGTH: - Average sentences per paragraph: [count] - Pattern: [short punchy/medium/long flowing] FORMATTING: - Uses bullet points: [frequently/occasionally/never] - Uses headers: [frequently/occasionally/never] - Uses bold/emphasis: [frequently/occasionally/never] TRANSITIONS: - Common transition phrases: [list] - Paragraph openings pattern: [observation] ``` ### Step 3: Score Each Dimension For each of the six dimensions, assign a score (1-10) with evidence: ```json { "dimension": "formality", "score": 6, "evidence": [ { "quote": "We're excited to help you get started", "source": "Homepage", "analysis": "Contraction 'we're' + 'excited' suggests casual-professional balance" }, { "quote": "Our team is dedicated to your success", "source": "About page", "analysis": "More formal phrasing, no contractions" } ], "conclusion": "Balanced formality (5-7 range) - professional but not stiff, uses contractions selectively" } ``` **CRITICAL: Every score needs evidence. No evidence = no score.** ### Step 4: Identify Patterns Across Samples Look for consistency and inconsistency: ```markdown CONSISTENT PATTERNS (appear in 80%+ of samples): - [Pattern]: [evidence across samples] INCONSISTENT PATTERNS (vary across samples): - [Pattern]: [note the variation and possible reason] ANOMALIES (one-off departures): - [Anomaly]: [where it appeared, possible explanation] ``` ### Step 5: Synthesize Voice Guidelines Convert analysis into actionable guidelines: ```markdown ## DO's (with examples) ### DO use contractions in conversational contexts - ✓ "We're here to help" - ✓ "You'll love this" - ✗ "We are pleased to inform you" ### DO lead with benefits - ✓ "Save 3 hours every week" - ✗ "Our software has automated scheduling" ## DON'Ts (with examples) ### DON'T use corporate jargon - ✗ "Leverage synergies" - ✗ "Best-in-class solutions" - ✓ "Work better together" - ✓ "Tools that actually help" ### DON'T be overly casual - ✗ "OMG you guys!!!" - ✗ "This is literally the best" - ✓ "We're genuinely excited about this" ``` --- ## Anti-Hallucination Rules for Voice Extraction ### Rule 1: Evidence or Nothing ``` ✗ WRONG: "The brand voice is friendly and approachable" ✓ RIGHT: "The brand voice appears friendly [Evidence: 8/10 sentences use 'you' directly, contractions in 70% of copy, exclamation points in 3/5 headlines - Source: Homepage analysis]" ``` ### Rule 2: Quote Don't Paraphrase ``` ✗ WRONG: "They tend to be enthusiastic" ✓ RIGHT: "Enthusiasm is present [Example: 'We absolutely love helping small businesses thrive!' - Source: About page, para 2]" ``` ### Rule 3: Note Sample Limitations ``` If only analyzing one sample: → State: "Based on limited sample (homepage only). Voice profile confidence: LOW. Recommend analyzing additional content before finalizing guidelines." ``` ### Rule 4: Distinguish Preference from Practice ``` If client says they want to sound "bold and edgy" but their content is conservative: → Flag: "[INCONSISTENCY: Stated preference is 'bold/edgy' but existing content scores 4/10 on directness. Clarify: Should new content match existing voice or shift toward stated preference?]" ``` ### Rule 5: Don't Invent "Competitor Voice" ``` ✗ WRONG: "Competitors tend to be more formal" ✓ RIGHT: "Competitor voice not analyzed - no competitor samples provided" OR ✓ RIGHT: "Competitor [Name] voice analyzed: [specific observations with quotes]" ``` --- ## Output Schema: Brand Voice Profile ```json { "profile_metadata": { "client_name": "", "created_date": "", "samples_analyzed": [ { "source": "", "type": "", "word_count": 0, "url": "" } ], "confidence_level": "high|medium|low", "confidence_notes": "" }, "voice_dimensions": { "formality": { "score": 1-10, "label": "Very Casual|Casual|Balanced|Professional|Very Formal", "evidence": [ { "quote": "", "source": "", "analysis": "" } ], "summary": "" }, "enthusiasm": { "score": 1-10, "label": "Reserved|Measured|Engaged|Energetic|Exuberant", "evidence": [], "summary": "" }, "humor": { "score": 1-10, "label": "Serious|Occasional Wit|Playful|Witty|Comedy-Forward", "evidence": [], "summary": "" }, "directness": { "score": 1-10, "label": "Soft|Gentle|Clear|Direct|Bold", "evidence": [], "summary": "" }, "technical_complexity": { "score": 1-10, "label": "Very Simple|Accessible|Moderate|Technical|Expert", "evidence": [], "summary": "" }, "warmth": { "score": 1-10, "label": "Distant|Neutral|Friendly|Warm|Intimate", "evidence": [], "summary": "" } }, "tone_guidelines": { "primary_tone": { "tone": "", "description": "", "evidence": "" }, "secondary_tones": [ { "tone": "", "when_to_use": "" } ], "tones_to_avoid": [ { "tone": "", "why_avoid": "" } ] }, "language_patterns": { "sentence_patterns": { "average_length": "", "preferred_structure": "", "uses_questions": true|false, "uses_exclamations": true|false }, "word_preferences": { "preferred_words": [ { "word": "", "example_usage": "", "source": "" } ], "avoided_words": [ { "word": "", "why_avoid": "" } ] }, "pronoun_usage": { "first_person": "we|I|our team|[brand name]", "second_person": "you|y'all|folks|customers", "evidence": "" }, "contractions": "always|usually|sometimes|rarely|never", "jargon_level": "none|minimal|moderate|heavy" }, "dos_and_donts": { "dos": [ { "guideline": "", "good_example": "", "source": "" } ], "donts": [ { "guideline": "", "bad_example": "", "good_alternative": "" } ] }, "application_notes": { "headlines": "", "body_copy": "", "ctas": "", "error_messages": "", "email_subject_lines": "", "social_media": "" }, "inconsistencies_flagged": [ { "observation": "", "sources": [], "resolution_needed": "" } ], "gaps_in_analysis": [ { "what_missing": "", "impact": "", "recommendation": "" } ] } ``` --- ## Verification Checklist Before finalizing voice profile: ### Evidence Check - [ ] Every dimension score has at least 2 supporting quotes - [ ] All quotes include source attribution - [ ] No scores based on assumption alone ### Consistency Check - [ ] Scores across dimensions form coherent picture - [ ] Any inconsistencies are flagged and explained - [ ] Stated preferences vs. actual practice are reconciled ### Completeness Check - [ ] All six dimensions scored - [ ] Do's and Don'ts have concrete examples - [ ] Application notes cover key content types ### Usability Check - [ ] Guidelines are specific enough to apply - [ ] Examples are clear and representative - [ ] A copywriter could use this to write on-brand content --- ## Integration Notes This skill is typically used by: - `client-discovery-agent` (during onboarding) - `landing-page-copywriter` skill (for voice-consistent copy) - `website-copywriter` skill (for voice-consistent copy) - `/voice` command (for voice extraction or application) Voice profiles should be saved to a consistent project location for downstream access. --- ## Quick Reference Card For rapid voice extraction when time is limited: ```markdown ## 60-Second Voice Scan Read 3 paragraphs of client content. Note: 1. FORMALITY: Contractions? (casual) or formal phrasing? 2. ENTHUSIASM: Exclamation points? Power words? Or measured? 3. HUMOR: Any wit/jokes? Or purely informational? 4. DIRECTNESS: "You should" (direct) or "You might consider" (soft)? 5. COMPLEXITY: Jargon? Or plain language? 6. WARMTH: "We care about you" or "Users will find"? Note 1 quote per dimension. That's your baseline. Flag: "Quick scan only - full analysis needed for production guidelines" ``` --- ## References For detailed examples and edge cases, see: - `references/voice-examples.md` - Sample voice profiles from various industries - `references/voice-edge-cases.md` - Handling difficult extraction scenarios --- Source attribution: David-Li0406 Original project: https://github.com/David-Li0406/meta-skill-evloving/blob/ca3a335628981df10c36e00cb9850df2c247ab9a/skill-flow/data/skills-refined-36k/skillsmp/brand-voice-extraction/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. 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See the License for the specific language governing permissions and limitations under the License. # Mega AI Hub resource metadata Creator / publisher: David-Li0406 Original project: https://github.com/David-Li0406/meta-skill-evloving/blob/ca3a335628981df10c36e00cb9850df2c247ab9a/skill-flow/data/skills-refined-36k/skillsmp/brand-voice-extraction/SKILL.md Attribution basis: Source repository record Fields of work: Content & Media, Design, Marketing Roles: Brand Strategist, Content Marketer, Copywriter, Marketing Analyst, UX Writer Specialties: Specialty not specified Tools: Tool not specified Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 05d1b5949d9ac76c4353b39ad118d623b24948cc3e1a5d701e864bfaae391cd6