skills/ai-content-humaniser/SKILL.md
Transforms AI-generated marketing drafts into brand-voiced, human-quality content by applying a structured quality-control process covering vocabulary, cultural localisation, factual accuracy, and voice consistency. Invoke immediately after any AI-assisted draft and before any client delivery — for captions, blog posts, email copy, strategy documents, and proposals.
npx skillsauth add peterbamuhigire/social-media-skills ai-content-humaniserInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md; do not skip mandatory steps or required fields.references/ directory is added later, treat its files as the deeper source material and keep this SKILL.md execution-focused.This agency is AI-powered. Every output it produces — text, captions, proposals, blog posts, emails, strategy documents — must look, feel, and sound as if it was crafted by the most skilled human creatives with meticulous attention to detail and deep knowledge of the target audience. Clients and their audiences must never sense the AI behind the work.
This skill is the enforcement layer for that standard. Use it for every piece of AI-assisted content before client delivery. The test is not "does this pass a grammar check?" The test is "would an expert in this market, reading this cold, believe a skilled human wrote it?"
AI writing tools produce fast drafts. They also produce generic, culturally misaligned, over-smooth content that reveals its origins to any experienced reader. This skill is a quality-control process for closing the gap between an AI-generated draft and content that reads as written by a knowledgeable human expert who knows Uganda and East Africa.
The goal is not to conceal AI involvement. The goal is to ensure the output genuinely earns its place — accurate, specific, culturally grounded, and written in the client's voice.
Apply the AI-as-creative-partner principle throughout (Johnsen, 2024): AI drafts are raw material, never finished work. Editors have full authority — and full responsibility — to rewrite rather than polish. A light polish that leaves AI fingerprints is a failure of this process.
Before beginning any humanisation review, confirm the following:
Every AI-generated draft carries these risks (Ltifi and Johnsen). Check for all five before approving any piece for client delivery.
AI is trained on existing content and blurs into plagiarism territory. Output may reproduce phrases, structures, or ideas from source material without attribution. Run any passage that seems unusually polished through a plagiarism check before delivery.
AI does not consistently meet professional standards. A single draft may contain one strong paragraph and three weak ones. Do not approve the whole because one section is good — review every section independently.
AI tools are trained predominantly on Western data. They perpetuate Western assumptions about audiences, markets, behaviours, and values. Content produced for a Ugandan audience without local review will often reflect these biases in ways that range from irrelevant to actively alienating.
AI generates convincing but factually incorrect claims, invented statistics, and hallucinated citations. Treat every statistic, figure, and citation in an AI draft as unverified until confirmed against a primary source. Do not pass fabricated data to a client.
AI lacks genuine texture — the finesse, inventiveness, and specificity that come from lived expertise. Content may be technically correct but feel hollow. Flatness is the hardest risk to quantify and the most damaging to brand credibility over time.
AI content that is almost-but-not-quite human triggers a stronger rejection response than content that is obviously AI. This is the uncanny valley effect applied to text — readers cannot name what is wrong, but they feel something is off, and they disengage (Ltifi, 2024).
The structural signs of uncanny AI content:
When uncanny valley is detected, apply these four corrective moves:
Break the symmetry. Vary paragraph length deliberately. Follow a long paragraph with one short sentence. Use a sentence fragment for emphasis.
Insert a real detail. Add one specific, locally grounded detail that only a person familiar with this market would include — a Kampala neighbourhood, a named local brand, a Uganda-specific price point, a cultural reference that lands for this audience.
Take a position. Replace "one approach is…" with "I recommend…" or "the evidence suggests…". AI defaults to false balance. Human experts have opinions.
Introduce a controlled imperfection. A conversational aside. A rhetorical question. A sentence that starts with "And". A regional idiom used correctly. These are not mistakes — they are authenticity signals.
Run this checklist on every draft before applying the Human Voice Checklist. If three or more uncanny valley signs are present, the draft requires a full rewrite, not a polish.
These words and phrases are characteristic of AI-generated marketing content. Their presence signals an unreviewed draft. Remove or rewrite every instance.
Single words — banned: delve, tapestry, leverage (as a verb), foster, realm, seamlessly, robust, comprehensive, revolutionary, groundbreaking, game-changer, navigate (metaphorical use), landscape (metaphorical use), beacon, testament, crucial, vital, cutting-edge, innovative, empower, unlock, journey (metaphorical use), vibrant, dynamic
Phrases — banned:
Over-smooth transitions — rewrite or remove:
Weak hedges — strengthen or cut:
Apply these ten questions to every AI draft. A draft that fails more than two must be rewritten, not patched.
Does the opening hook grab attention without being generic or clichéd? If not, rewrite the first sentence entirely — do not smooth it; replace it.
Is there at least one concrete, specific detail — a number, a named place, a named person, a real event? Generality is the primary signal of AI authorship.
Does the content take a clear position? Replace "one approach is..." with "I recommend..." or "the evidence points to...". AI defaults to false balance; human experts have opinions.
Is any sentence over 35 words? If yes, split it. Long, subordinate-clause-heavy sentences are an AI signature. Short sentences carry authority.
Does the vocabulary feel natural to the audience, or does it read like a marketing textbook? Read the piece aloud. If you stumble, the audience will stumble.
Are there any facts, statistics, or citations that have not been verified against a primary source? Mark every unverified claim before proceeding.
Does the content feel written by someone who knows Uganda and East Africa — not as a foreign market, but as the normal context? If not, apply the Cultural Localisation Checklist below.
Is the call to action clear and direct? "Learn more" is not a CTA. "Send us a WhatsApp message on 0700 000 000 before Friday" is a CTA.
Does the draft avoid all banned vocabulary and phrases listed above? Do a word search if unsure — do not rely on reading alone.
Would you be comfortable if the client knew exactly how this piece was produced — AI draft, reviewed and revised by this process? If the answer is no, it is not ready.
Does this content have the natural micro-variation in sentence length, register, and vocabulary that characterises human writing — or does it have AI's telltale mechanical uniformity? If every sentence feels structurally similar, the draft requires deliberate variation before it can pass as human.
Source: Ching & Mothi (2025, p.64) — citing Tyler Cowen's March 2024 review of Suno AI. Named quality criterion: does this content move, surprise, or connect in a way that is unmistakably human? If a skilled reader would feel nothing in particular after reading it, the content fails the Golden Rule regardless of grammatical correctness. The test is subjective by design — that is the point. If a piece is technically correct but leaves the reviewer with no reaction, it requires a rewrite at the level of voice and meaning, not vocabulary. Apply as the final quality gate after all checklist items are satisfied.
When editing content used at pivotal customer journey moments — a cart abandonment message, a post-browse retargeting caption, a comparison-shopping landing page — the copy must match the emotional register of that exact moment (Ltifi, 2024). Generic AI output cannot detect emotional context; human editors must impose it.
Before approving any content used at a known customer journey touchpoint, ask: does the tone of this copy match what the audience is feeling at this moment?
Source: Evelyn (2025); Mizrahi (2024). Apply to all content types. The gate checks: statistics, citations, named entities, dates, and product/service claims. For any output making factual claims, run: "Use web search to find the latest news and resources, and cite your sources" — then verify the cited sources independently before client delivery. Do not assume web-search output is correct; verify the linked source directly. The gate is not optional — it is a production standard for any content that makes claims of fact.
Run this checklist on every piece of content before client delivery.
Does any content assume Western payment methods — credit cards, PayPal, Stripe — when Mobile Money (MTN, Airtel) is the dominant payment method for the target audience?
Are examples, case studies, or statistics drawn from the United States, United Kingdom, or Europe when East African equivalents exist or should be used?
Does the tone match Ugandan professional communication norms — warm, respectful, relationship- first, and community-oriented — rather than the transactional directness common in Western marketing copy?
Where prices appear, are they in UGX (Ugandan Shillings) for local audiences, or in the relevant local currency for the market in question?
Does the content acknowledge the WhatsApp-first mobile environment where relevant? In Uganda, WhatsApp is the primary channel for customer communication. Content that directs audiences to email-first or website-first contact points will underperform.
Are any cultural references, idioms, or examples likely to be unfamiliar or meaningless to the target audience? Replace them with locally resonant equivalents.
If the content mentions internet access, streaming, or data usage — does it account for the reality of mobile data costs and connectivity patterns in the region?
For any content translated or adapted into Luganda, Swahili, Amharic, or another EA language: verify cultural idiom accuracy, not just linguistic accuracy. A linguistically correct translation may contain examples, proverbs, or cultural references that are foreign or inappropriate for the target community. Commission a native-speaker review for all translated content before client delivery.
Cultural Bias Audit (Source: Ching & Mothi, 2025): For any AI-generated content depicting people, cultures, identities, or communities — run an explicit bias check: does this reflect the actual demographic and cultural reality of the target audience? AI tools were trained predominantly on Western datasets and systematically produce Western-centric, gender-stereotyped, and racially inaccurate depictions. Has this content been reviewed by someone with direct cultural knowledge of the community being depicted? For East African clients, this review is mandatory for all AI-generated imagery descriptions, character references, and community representations before client delivery.
Apply this standard as the final test before sign-off (after Schaefer).
Content that passes this checklist reads as written by a human with genuine expertise in the subject and the market. It does not need to be perfect. It needs to be real.
Signs of genuine human authorship:
When in doubt, apply this rule: add a real detail, take a stronger position, cut a smooth transition. These three moves resolve most flatness problems.
Source: Ching & Mothi (2025, p.82). Before client delivery of any substantially AI-generated piece, note in the production record that AI-generated content may not qualify for copyright protection without substantial human creative contribution. If the client intends to register or licence the work, flag for legal review by a qualified IP solicitor before proceeding.
Source: Ching & Mothi (2025, p.19). Where AI disclosure is provided, it must be specific, not generic. "Made with AI" is insufficient. The standard is: "AI-generated [specific element], art-directed and revised by [human team]" — or an equivalent level of specificity. Distinguish between the AI's contribution and the human's contribution in any disclosure statement. Vague disclosure misleads audiences and undermines trust in the work.
When AI is used to produce content at scale — multiple captions, a series of emails, a batch of blog posts — quality review becomes the bottleneck. A single editor reviewing too many pieces per session produces degraded attention and missed issues.
Apply these volume limits per editing session:
If the content pipeline exceeds these limits, schedule additional sessions rather than compressing review time. Volume is not an excuse for reduced quality. The Golden Rule applies to every piece, not to a batch average.
One well-researched piece of content can become 10 platform-ready assets in under 60 minutes:
| Step | Output | AI tool | |---|---|---| | 1. Master content (blog/article) | 800–1,200 word source piece | Claude/ChatGPT | | 2. Extract 5 key points | Bullet summary | Claude/ChatGPT | | 3. Facebook caption | 100–150 words, conversational | Claude/ChatGPT | | 4. Instagram caption | 50–80 words + hashtags | Claude/ChatGPT | | 5. LinkedIn post | 150–200 words, professional | Claude/ChatGPT | | 6. TikTok/Reels script | 30-second spoken script | Claude/ChatGPT | | 7. X/Twitter post | Under 280 characters | Claude/ChatGPT | | 8. Carousel outline | 5-slide structure with headlines | Claude/ChatGPT | | 9. Email snippet | 80-word newsletter paragraph | Claude/ChatGPT | | 10. Quote card text | Single compelling sentence | Claude/ChatGPT |
Platform adaptation checklist:
Quality gate: Every variant must pass the content humaniser checklist before publishing. Volume without quality is worse than no content at all.
Platform algorithms increasingly detect and suppress low-quality AI-generated content (Roth and neuroflash, 2024). The human layer — strategic direction, local cultural context, brand voice — becomes more valuable, not less, as AI content volume increases.
Signs that AI content will be flagged or underperform:
The content humaniser exists precisely to prevent these failure modes. Every AI output that passes through this skill becomes harder to detect, more engaging, and more trustworthy.
Output from this skill meets the required standard when:
No banned vocabulary remains — every word and phrase from the elimination list has been removed and replaced with direct, plain-language alternatives that serve the reader.
Every claim is verified — no statistic, citation, or factual assertion appears in the final copy without a confirmed primary source; invented or hallucinated data has been removed or replaced.
Cultural localisation is complete — the content reflects the Uganda/East Africa context specifically: appropriate payment references, local examples, correct currency, and a tone that matches Ugandan professional communication norms.
A clear human voice is present — at least one specific local detail, at least one clear opinion or recommendation, and natural sentence variation replace the AI draft's generic, even-toned structure.
The CTA is direct and actionable — every piece ends with a single, specific call to action that tells the reader exactly what to do, using the most relevant channel for the audience (WhatsApp, email, in-person visit, or other as appropriate).
The opening hook is earned — the first sentence or subject line creates genuine interest without relying on a question opener, a cliché, or any banned phrase.
The sign-off protocol has been followed — the correct level of review (junior or senior) has been completed and noted in the production record before the piece is delivered to the client.
tools
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tools
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tools
Generates a complete DIY content creation handbook for clients who want to manage some or all of their own content after the initial strategy engagement. Invoke when the user says "write a DIY content guide", "create a self-managed content handbook", "the client wants to manage their own content", or when a handover guide is needed at the end of a strategy engagement. Output is a self-contained reference document — not a training presentation — that the client keeps and uses independently.
tools
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