brand-voice-ai-training

name	brand-voice-ai-training
description	Use when Brand Voice AI Training is needed to produce a brand voice AI training deliverable for social-media or digital-marketing work; use `ai-readiness-diagnostic` when its narrower outcome is requested.
metadata	{"portable":true,"compatible_with":["claude-code","codex"]}

Brand Voice AI Training

Use When

• Use this skill when the requested outcome is specifically a brand voice AI training deliverable and the supplied brief falls within brand voice ai training.

Do Not Use When

• Use ai-readiness-diagnostic when its narrower output is the real deliverable; do not use this skill as a generic substitute.
• Do not use it to publish, send, spend, alter a live account, or make unsupported legal, platform, performance, or certification claims.

Required Inputs

Artefact	Source/provider	Required?	If absent
AI marketing use-case brief, intended human control point and success measure	Requester or approved brief	Yes	Stop and request the missing decision context.
Brand voice, offer facts, constraints and approvals	Client source pack or authorised owner	Conditional	State assumptions; do not invent names, prices, results or approvals.
Performance, platform or research evidence used for claims	Traceable export, URL, document or named source	Conditional	Draft the narrowest reviewable version and flag the missing evidence.

Capability and Permission Boundaries

Drafting is permitted within the supplied brief. Publishing, sending, spending, changing live accounts, or claiming certification requires separate explicit authority. Minimum capabilities are read access to supplied files and search across the authorised evidence set. Use only the files, tools, accounts and evidence made available for the engagement, expose every unassessed check, and obtain explicit authority before any mutation.

Degraded Mode

Fallback: if files, network access, platform data, language review or production tools are unavailable, return the narrowest useful qualified brand voice AI training deliverable; mark unavailable checks not assessed and never convert them into a pass.

Decision Rules

Choice	Action	Failure or risk avoided
Data readiness, AI maturity and risk support the proposed operating level	Choose the lowest viable automation level and define its human approval gate.	Automating an unsafe or unevaluable marketing process.
A required fact or approval is missing	Stop that claim or action; request it or use an explicit placeholder.	Fabricated facts, implied consent or unauthorised publication.
Evidence is partial but a useful draft is possible	Deliver a qualified draft with gaps and the next verification step.	Treating an unassessed requirement as passed.

Workflow

1. Confirm the exact brand voice AI training deliverable, consumer, market, channel and approval boundary; route to ai-readiness-diagnostic if it is the closer match.
2. Inventory supplied facts, source provenance, constraints and missing inputs; stop if the objective, audience or authority is unknowable.
3. Select the domain method and record the material decision behind it before drafting.
4. Produce the smallest complete brand voice AI training deliverable; keep facts traceable and placeholders visibly unresolved.
5. Test the result against the decision table, domain quality criteria and anti-slop gate; recover by narrowing or qualifying unsupported portions.
6. Deliver the artefact with evidence, assumptions, unassessed checks and the next approval or verification step.

Outputs

Artefact	Consumer	Observable acceptance condition
Brand voice ai training deliverable	Requester, client reviewer or delivery team	The brand voice AI training deliverable addresses the named audience and objective, records assumptions, and passes the skill's domain checks without invented facts.
Decision and gap note	Approver or next workflow	Names the chosen route, evidence used, unresolved inputs and any action requiring authority.

Evidence Produced

Evidence	Format	Acceptance condition
Source/assumption register and completed release checklist	Inline table, checklist or linked source note	Every material claim, decision and unavailable check is traceable.

Quality Standards

• Preserve the domain guidance and East African market context below; replace it only when the requester names another market.
• Use British English unless the target language or market requires otherwise, and verify names, figures, quotations and platform rules before use.
• Make the key choice visible, cover failure and edge cases, and keep the result ready for its named consumer.
• Run the repository's anti-ai-slop ship gate; a blocking factual, cultural, safety or permission defect stops release.

Anti-Patterns

• Writing before the objective and audience are known. Fix: stop and obtain the missing brief fields.
• Reusing a neighbouring skill's template because the headings look similar. Fix: route by the requested brand voice AI training deliverable, not vocabulary overlap.
• Adding a price, result, quotation, platform limit or cultural claim without a traceable source. Fix: verify it or qualify/remove it.
• Treating missing access, evidence or native-language review as approval. Fix: mark the check not assessed and narrow the result.
• Publishing, sending, spending or changing a live account from drafting authority alone. Fix: obtain explicit action-specific authority and retain the approval record.

References

• ai-readiness-diagnostic is the nearest routing comparison for this skill.
• Repository agent guide defines the engine-wide market, safety and anti-slop gates.

Why This Matters

AI tools default to a generic global register. The output is professional, grammatically correct, and completely bland. Left untrained, repeated AI use gradually smooths out a brand's authentic character — the local references, the signature phrases, the particular warmth or edge that makes a brand recognisable.

The Brand Context Block is the solution. It is a structured prompt header, pasted before every AI instruction, that gives the tool the context it needs to write in the client's voice rather than in the voice of a marketing textbook. One well-built block transforms every AI session for this client.

Without it: every session starts from scratch. Generic output. Client frustration. With it: consistent, on-brand content from the first line, every time.

This skill works with any AI tool — Claude, ChatGPT, Gemini, or any future equivalent.

Required Inputs

Before beginning, collect or confirm the following. If 04-brand-voice-intake has already been completed for this client, pull the relevant answers from there rather than asking again.

Input	Detail
Client business name	Trading name as used publicly
Industry	Sector and sub-sector
Country / city	Defaults to Uganda/East Africa if not specified
Primary goal	What this client most needs consistent AI content for
Sample content	3–5 pieces of existing content that feel most "them" — posts, emails, web copy, WhatsApp messages
Voice adjectives	Exactly 3 adjectives describing the brand voice
We are / not pairs	3 pairs: "We are [X], not [Y]"
Always-use vocabulary	5–10 words or phrases the brand always uses
Never-use vocabulary	5–10 words or phrases the brand avoids
Tone position	Where on the scale: Formal ←→ Conversational
Cultural references	Local language phrases, local slang, community references central to their identity
Emoji policy	Yes / No / Limited (and if limited, which contexts)
Content types produced	Which formats need few-shot examples: captions, emails, Stories/WhatsApp Status, DM replies, other

Step 1 — Capture the Voice Inputs

Ask the client for each item in the Required Inputs table above, or pull from 04-brand-voice-intake.

On sample content: the 3–5 pieces must be content the client themselves considers most representative — not the highest-performing post, but the one that sounds most like them. Performance and authenticity do not always overlap.

On cultural references (EA-specific): ask whether the brand uses local language phrases (Luganda, Swahili, Runyankole, or others depending on region), local slang, references to local events, seasons, or community structures. These are often the most distinctive elements of an East African brand voice and the first things a generic AI strips out. Preserve them explicitly.

On tone position: use a simple five-point label to avoid ambiguity:

1. Formal — professional, measured, institutional
2. Mostly formal — professional with occasional warmth
3. Balanced — professional but approachable
4. Mostly conversational — warm, direct, light
5. Conversational — casual, familiar, energetic

Ask the client to pick one, then ask for a single sentence from their existing content that best represents that tone.

Step 2 — Analyse the Sample Content

Do not rely solely on what the client tells you their voice is. Read the sample content and extract what it actually is. Clients often describe an aspirational voice, not their real one.

Analyse the samples for:

• Sentence length — are most sentences under 15 words, or longer and more considered? Count roughly.
• Questions vs. statements — how frequently do they open with a question? What kind of question — rhetorical, direct, invitational?
• How they address the customer — "you", "our community", first name, "fellow [identity]", or something else?
• Active vs. passive voice — count active constructions vs. passive. Most strong brand voices are predominantly active.
• Recurring phrases — are there phrases or sentence structures that appear more than once across the samples? These are signature patterns and must be preserved.
• Hook style — how do posts open? With a claim, a question, a number, a story, a challenge?
• CTA style — how do posts close? Soft invitation, direct instruction, question, emotional close?
• Humour or wit — present or absent? If present, what type — self-deprecating, dry, warm, playful?
• Local language use — if present, in which positions (opening hook, emphasis, sign-off) and how frequently?

Record findings in a short analysis note before building the block. This is internal reference — not delivered to the client.

Step 3 — Build the Brand Context Block

The Brand Context Block is the deliverable. Produce it using the template below, populated with everything gathered in Steps 1 and 2.

BRAND CONTEXT — [Client Name]
You are writing for [Business Name], a [one-sentence description] based in [location].

VOICE: [Adjective 1], [Adjective 2], [Adjective 3].
We are [X], not [Y].
We are [X], not [Y].
We are [X], not [Y].

TONE: [Tone level 1–5 with label]. Example of our tone: "[paste one sentence from their content]"

ALWAYS USE:
- [Signature phrase or word]
- [Signature phrase or word]
- [Signature phrase or word]
- [Signature phrase or word]
- [Signature phrase or word]
[Add up to 10 total]

NEVER USE:
- [Client-specific banned word or phrase]
- [Client-specific banned word or phrase]
- [Client-specific banned word or phrase]
[Add client specifics, then append the standard ban list below]
- delve
- tapestry
- landscape (when used metaphorically)
- leverage
- navigate (when used metaphorically)
- foster
- realm
- game-changer
- revolutionary
- groundbreaking
- comprehensive
- robust
- seamlessly
- "in today's digital age"
- "in the ever-evolving world of"
- "it is worth noting"
- "it is important to note"
- furthermore
- moreover

AUDIENCE: [Who they are writing for — demographic, what they care about, what they already know, what language they use]

PLATFORM: [Platform this session is for — Facebook / Instagram / LinkedIn / WhatsApp / X / email / other]

CULTURAL CONTEXT: [Local language phrases in use, regional references, community identity markers — delete this field if none apply]

EMOJI POLICY: [Yes — use freely / No — do not use / Limited — use only in [specified contexts]]

EXAMPLES OF OUR VOICE:
"[2–3 sentences from their best existing content — paste verbatim, do not edit]"

TASK: [The specific content request follows here]

Critical notes on the template:

• Every field is mandatory. If a client has not supplied a value, go back and ask rather than leaving it blank or inventing a placeholder.
• The EXAMPLES OF OUR VOICE field is the most important field in the block. Paste real, verbatim content. This single section does more work than all the adjectives combined.
• Minimum three examples standard (Source: Evelyn, 2025, p.71; Mizrahi, 2024): Provide a minimum of three separate examples in the EXAMPLES OF OUR VOICE field. Two examples produce inconsistent voice replication. Three or more enable the AI to reverse-engineer voice characteristics reliably — including sentence rhythm, structural habits, and register — that cannot be described in words alone. Fewer than three examples is the most common reason a Brand Context Block underperforms on live client work.
• The PLATFORM field changes with every session. Keep the rest of the block fixed and update only this field when switching platforms.
• The standard AI vocabulary ban list is included in every block for every client, without exception. Add client-specific banned terms on top of it.

Character-Voice Differentiation (Highly Distinctive Brands)

Source: Donovan, S. (2019) 5,000 Writing Prompts: A Master List of Creative Exercises. For clients with highly distinctive, idiosyncratic voices — founders who write in a recognisable personal style, brands with a cult following, or professional voices with known stylistic signatures — add an optional STYLISTIC BANS field to the Brand Context Block. This goes beyond vocabulary to structural habits the brand avoids:

STYLISTIC BANS:
- Never opens with a statistic
- Never uses a list of three where a paragraph would be stronger
- Never starts a post with a question
- Never closes with a sentence beginning "Remember:"
- Never uses em dashes for dramatic pauses

The principle: specify what the voice does NOT do as precisely as what it does. The most distinctive voices are as defined by what they refuse as by what they embrace. Vocabulary bans catch words; stylistic bans catch habits of structure and rhythm that are invisible to the vocabulary scanner but obvious to a careful reader.

Add this field only for clients where voice distinctiveness is material to brand value. For standard SME clients, vocabulary and example-based training is sufficient.

Step 4 — Few-Shot Examples by Content Type

For each content type the client regularly produces, source 1–2 approved examples in their voice. These are stored alongside the Brand Context Block and pasted into the prompt when working on that content type.

Caption example One caption that performed well and that the client considers representative. Include the platform it was written for.

Email opening example The first 3–4 sentences of an email the client considers on-brand. Subject line included if available.

Story / WhatsApp Status script example One short script (3–5 frames or lines) for ephemeral content. If the client does not use Stories or WhatsApp Status, skip this.

Response to a comment or DM example One example of how the brand replies to a positive comment and one for a neutral enquiry. Tone in replies often differs from broadcast content — capture both.

Blog or long-form opening example (if applicable) First paragraph only. Enough to establish rhythm and hook style.

Store all few-shot examples in a single reference document in the client's project folder, labelled clearly by content type.

Step 5 — Quality Test the Block

Before the block is used in live client work, run a quality test.

Test prompt: Using only the Brand Context Block (no few-shot example), ask the AI to write one piece of content the client produces regularly — a Facebook caption, an email opening, a WhatsApp message.

Compare the output against 2–3 pieces of the client's existing approved content. Ask:

• Does this feel like this brand, or does it feel generic?
• Is the vocabulary matching — are the signature phrases appearing naturally?
• Is the tone right for the platform and for this client's position on the scale?
• Are the banned words absent?
• Would the client recognise this output as theirs without being told the AI wrote it?
• Does local language appear where appropriate, or has the AI defaulted to Standard English only?

If the output fails any of these checks:

• Add more verbatim examples to the EXAMPLES OF OUR VOICE field — this is almost always the fix.
• Make the NEVER USE list more specific — add the exact generic phrases that appeared in the failing output.
• Tighten the "We are X, not Y" pairs to address the specific failure mode observed.
• Re-run the test after each refinement. Iterate until the block passes.

Document which version passed the quality test. Label it v1.

Voice Replication Comparison Test

Source: Mizrahi (2024). When testing the Brand Context Block, run two versions of the same prompt:

Method 1 — Adjectives and "We are X, not Y" only (no EXAMPLES OF OUR VOICE field): Generate one piece of content using only the VOICE, TONE, ALWAYS USE, NEVER USE, and AUDIENCE fields.

Method 2 — Full block including examples: Generate the same piece using the complete Brand Context Block with the EXAMPLES OF OUR VOICE field populated with three or more verbatim examples.

Compare the two outputs. Document which produces more accurate voice replication. If Method 1 significantly underperforms, the block needs more examples before it is deployed on live client work. This test is the single most reliable diagnostic for a Block that is technically complete but still producing generic output.

Step 6 — Maintain and Update the Block

The Brand Context Block is a living document, not a one-time deliverable.

Storage: save the block as a plain text file in the client's project folder. Name it [ClientName]-brand-context-v1.txt. Keep all versions.

Scheduled review: review the block quarterly, or immediately after any of the following:

• The client rebrands (name, positioning, visual identity, or audience shift)
• The client launches a new product line or service that requires a distinct tone
• Voice drift is detected (see below)

Detecting voice drift: if recent AI-assisted content is drifting toward generic — if it sounds more like a marketing textbook than like the client — the block needs updating. Signs of drift include: banned words reappearing, overly formal constructions, loss of local references, CTAs that feel transactional rather than relational.

Updating the block:

• Add new signature phrases as they emerge in the client's organic content.
• Add new banned terms as generic AI patterns appear.
• Replace EXAMPLES OF OUR VOICE with more recent content if the brand has evolved.
• Increment the version number (v1 → v2). Keep the previous version on file in case the update makes output worse.

Do not delete old versions. Reverting is sometimes necessary.

Quality Criteria

Output from this skill meets the standard when:

• The Brand Context Block is complete — no field is blank or contains a placeholder; every item in the Required Inputs table is represented.
• The EXAMPLES OF OUR VOICE field contains verbatim, unedited client content — not paraphrased or improved versions.
• The standard AI vocabulary ban list is present in full, with client-specific terms added above it.
• A quality test has been run and documented, and the block has been refined until AI output is indistinguishable in voice from the client's approved content.
• Few-shot examples cover every content type the client regularly produces, stored and labelled separately.
• Local language, cultural references, and EA-specific identity markers are preserved explicitly in the block, not left to the AI to infer.
• The block is versioned, stored in the client's project folder, and a review schedule is agreed (quarterly minimum).
• The block is platform-agnostic in its fixed fields, with only the PLATFORM field updated per session.