copywriting-tone-of-voice-creator

Skim references/discovery-questionnaire.md — it contains the exhaustive 80+ question bank. The batches below are the minimum to produce a usable TONE.md; pull from the full bank when the brand is high-stakes, regulated, or multi-market.

1. Glob for SOUL.md in CWD. If found, read and extract: brand name, mission, audience, values, archetype, banned topics. Display the extraction and ask the user to confirm or correct. Skip the questions that SOUL.md already answers.

2. Batch A — basics (single question-tool call, 4 questions):

   • Mode: Create from scratch / Adapt existing TONE.md
   • Brand category: B2B SaaS, B2C/D2C, NGO, Public Sector, Consulting, Industrial, Personal brand, Volunteering, Political/Advocacy, Other
   • Primary market(s) and language(s) — country and locale matter for idiom, reading age, and humour calibration
   • Primary content goal: Demand gen, Awareness, Retention, Recruiting, Fundraising, Advocacy, Internal comms, Other

3. Batch B — audience & channels (4 questions):

   • Primary audience (single persona, free text — multi-persona handled in follow-up)
   • Channels in scope (multi-select): Web, Blog, Email, LinkedIn, Twitter/X, TikTok, Instagram, YouTube, Podcast, In-product UI, Support, Press, Sales decks, Recruiting, Other
   • Reading-age target: Adult general / Expert+technical / Reading-age 9 (gov + inclusive default) / Mixed
   • Risk tolerance: Safe & neutral / Moderately distinctive / Boldly distinctive (willing to alienate non-buyers)

4. Batch C — personality & references (4 questions):

   • Primary archetype guess: 12 Jung options (Innocent, Sage, Explorer, Outlaw, Magician, Hero, Lover, Jester, Everyman, Caregiver, Ruler, Creator) or Unsure
   • Voice references: 3-5 admired brands to triangulate from (free text)
   • Anti-references: 3-5 brands NOT to sound like (free text)
   • Founder/CEO voice contribution: Heavy / Moderate / None / Explicitly avoid

5. Batch D — constraints (3-4 questions):

   • Regulatory regime: None / GDPR / HIPAA / FDA / SEC / FCA / ASA / Other
   • Cultural taboos and topics to avoid (free text)
   • Existing brand book / banned-word list (path or None)
   • Localisation strategy: Single locale / Multi-locale with shared voice / Per-locale voice

If the user's category is "Other" or sits outside the covered set in references/category-adaptations.md — politics, religious organisations, defense, gaming, healthcare professional comms, adult content, sports teams, fintech-crypto — proceed to Phase 2.

Spawn an Agent sub-task with this brief:

Research current tone-of-voice norms for <category> brands in <market>. Cover: 1) typical voice attributes for the category; 2) common pitfalls and how audiences react to off-tone copy; 3) 2-3 reference brands with publicly observable voice patterns (cite primary sources); 4) regulatory, cultural, or platform constraints on voice. Report in under 700 words with sources cited inline.

For broad cross-market research (e.g. political comms across regions), spawn up to 3 parallel agents split by region or sub-category, then synthesise the findings before continuing to Phase 3.

Use the agent's output to populate the category-adaptation section of TONE.md and refine voice attributes. Footnote sources — future maintainers will need to verify when category norms shift.

Use ultrathink for this phase. Synthesise the discovery inputs into:

1. NN/g 4 dimensions position — funny/serious, formal/casual, respectful/irreverent, enthusiastic/matter-of-fact. Each is a 3-point scale. Do not cluster all four near midpoint — defaulting to mid-range scores produces bland, forgettable voices that fail to differentiate from category default. Lean to one side on at least three of the four dimensions.

2. 3-5 voice attributes, each in the "X but never Y" pattern (Slack: "Confident, never cocky; Witty, but never silly"). For each, produce: one-line definition, 3 do's, 3 don'ts, 1 example sentence, 1 anti-example pulled from the brand's own past content if possible. Three is the minimum (fewer is unhelpful); five is the maximum (more is unmemorable). See references/voice-attributes.md for the documentation pattern.

3. Primary archetype (optional secondary). Don't over-commit to archetype — it is a positioning shortcut, not a voice solution. Brands that lean too hard on archetype end up in cosplay (every "Hero" brand sounds the same).

4. Tone modulation matrix — rows are situations (launch, crisis, complaint, win, sensitive topic, routine, sales objection, layoffs/bad news, apology), columns are the channels in scope. Each cell: dominant tone + 2-3 prohibited tones. This is the operational core — downstream writers and bots consult this more than the principles narrative.

5. Lexicon — preferred terms (named concepts, customer noun like "members" vs "users"), banned terms (jargon, marketing clichés, exclusionary language), power words (10-30), jargon policy (when allowed for which audience), naming conventions (brand, product, features, competitors). See references/lexicon-mechanics.md.

6. Mechanics — person (1st plural "we" / 2nd "you"), contractions (yes/no/contextual; GOV.UK avoids negative contractions because they harm non-native readers), Oxford comma, sentence length norm (general public: average 15-20 words; expert audiences may go longer), active/passive default (active unless softening a sensitive message), sentence case vs title case, emoji policy, punctuation tics (ellipses, em-dashes, exclamation marks), numerals. Same reference file.

7. Inclusive language — base on the Conscious Style Guide (Karen Yin) and APA Inclusive Language Guidelines. Decide gendered language policy, ability/disability terms, race, age, nationality, neurodiversity. Per market if multi-locale.

8. Channel-specific guidance — apply references/channel-adaptations.md per channel in scope, capturing hard platform constraints (character limits, format) and tonal shifts.

Use assets/TONE-template.md. Fill every section. Section names and structure are stable — downstream skills depend on them for parsing.

Mandatory sections (order matters for downstream pipelines):

• Context (brand, market, channels, goal)
• Voice attributes (3-5, each with do/don't/example/anti-example)
• Archetype
• NN/g 4 dimensions positioning
• Tone modulation matrix
• Lexicon (preferred, banned, power words)
• Mechanics
• Inclusive language
• Channel-specific guidance (one subsection per channel in scope)
• Global Do's and Don'ts (consolidated, scannable list — this is what writers paste into their context window when drafting)
• Examples library (before/after pairs)

Run these checks before finalising the file. If any fails, surface the gap and ask the user before writing the final TONE.md:

• 3-5 voice attributes — neither fewer nor more.
• Every attribute has at least one anti-example sourced from the brand's own context (not a generic placeholder like "lorem ipsum bad").
• NN/g positions don't all cluster near midpoint — at least 3 of 4 dimensions clearly off-centre.
• Banned-words list is non-empty (prevention is cheaper than prescription — without it, writers default to category clichés the brand wanted to avoid).
• One channel-specific subsection per channel in scope.
• Sample three random do's and three random don'ts and re-read: would a new writer or bot know exactly what to do tomorrow? If they're abstract, rewrite them as concrete sentences with examples.