conversion-copywriting
Skill1 starsChanged 29 days agoMITView on GitHub
This skill should be used when writing or rewriting customer-facing copy: product pages, landing pages, hero/headline sections, CTAs and button microcopy, email bodies, and ad copy. Trigger phrases include "write copy for", "rewrite this", "make this punchier/clearer", "headline for", "CTA for", "hero section", "product description", "ad copy", or "this copy is weak". Use it whenever copy quality affects conversion, even if the user does not name a framework.
2 other projects use a version of this.
Adopted by
Most recently taken up by
- novatic-cu/nova-skillstheir own version, first seen Sep 20, 2026
- leadgenjay/claude-skillstheir own version, first seen Jun 19, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- leadgenjay/claude-skills★ 22same name
- novatic-cu/nova-skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository7 other files it gives its agents.
- deep-research-synthesisSkill
- ecommerce-cro-auditSkill
- experiment-designSkill
- getting-startedSkill
- outbound-and-positioningSkill
- report-information-designSkill
- voc-researchSkill
The file
We split this skill into the rules it gives an agent
7 rules. About 0 are common, 4 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 17
Write copy that earns the next scroll, the next click, the sale.
- Very specific: line 24
Voice: confident, warm, non-hype: No corporate-speak, no exclamation-point inflation.
- Distinctive: line 29
No one, human or model, reliably predicts the winner: GPT-4 picked the winning Upworthy headline 38–40% of the time vs 33% by chance (Ye et …
- Very specific: line 41
Every headline is checked against Useful, Urgent, Unique, Ultra-specific.
- Very specific: line 45
Pull customer language first: Use the voc-research language bank (or mine reviews/survey answers) for the exact phrases customers use for …
- Distinctive: line 49
Add proof (social proof, specifics) and risk-reversal near the CTA.
- Distinctive: line 62
Don't invent proof, testimonials, or stats.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Conversion Copywriting
Write copy that earns the next scroll, the next click, the sale. Clarity over cleverness; desire first, proof second; every word earns its place.
Principles
- Clarity is the conversion lever. A reader who has to decode a sentence leaves. Simple words, short sentences, one idea per line.
- Lead with desire/benefit, justify with proof. Open on the outcome the reader wants; bring features, specs, and credentials in as the rational backup.
- Specific beats vague. Numbers, names, concrete detail. "Recovered $340K in 90 days" beats "drives results."
- One job per asset. A page, an email, an ad each has a single primary action. Cut anything that competes with it.
- Voice: confident, warm, non-hype. No corporate-speak, no exclamation-point inflation. (Chykalophia voice rules, including no em dashes, in
references/voice-and-headlines.md.)
What the evidence says about AI and copy
- AI-written copy and creative can match or beat human work in live tests: fully AI-generated display ads lifted CTR up to 19% over expert ads, while AI edits to human ads did not help (Lee, Ghose, Todri & Adamopoulos, NYU Stern 2025).
- Telling people an ad is AI-generated cut CTR by 31.5% (same NYU study). Don't add "AI-written" framing to the copy itself; follow any platform or legal disclosure rules that apply.
- No one, human or model, reliably predicts the winner: GPT-4 picked the winning Upworthy headline 38–40% of the time vs 33% by chance (Ye et al., Marketing Science 2025). Frameworks and the 4 U's are a quality floor, not a predictor.
- So the default output is a variant set for testing, written from customers' own words.
Pick the framework to the format (references/copy-frameworks.md)
- PDP / product page: PAS or FAB for the body, 4 U's headline, proof + risk-reversal blocks.
- Landing page (one offer): BAB or 4 Ps, or AIDA for the full-page arc.
- Email: PAS hook, one job per email, 4 Ps for offer emails.
- Ads: PAS or AIDA, ruthless brevity.
- Homepage / brand: StoryBrand SB7 (customer is the hero, brand is the guide).
- Long-form sales / consulting narrative: PASTOR.
Default headline test: the 4 U's
Every headline is checked against Useful, Urgent, Unique, Ultra-specific. Hit at least three; "useful + ultra-specific" is non-negotiable. Details and templated families in references/voice-and-headlines.md.
Workflow
- Identify the reader's awareness stage, the one job, and the single most compelling outcome.
- Pull customer language first. Use the
voc-researchlanguage bank (or mine reviews/survey answers) for the exact phrases customers use for the problem, the outcome and their objections. Copy built from these phrases is the default; invented phrasing is the fallback. - Choose the framework for the format; draft to it.
- Write 3–5 variants per key element (headline, subhead, CTA, key benefit block). Make each variant differ on one lever (e.g. outcome vs objection-handling vs proof-led), and label the hypothesis it tests and the customer evidence it draws on. Run the 4 U's as a floor on each. Hand the set to
experiment-designfor sizing; if traffic can't support a test, recommend the variant with the strongest customer evidence and say that is the reason. - Apply the voice rules (cut hedging, buzzwords, em dashes, exclamation points; make verbs strong and nouns specific).
- Add proof (social proof, specifics) and risk-reversal near the CTA; end with one clear action.
Reference map
references/copy-frameworks.md— AIDA, PAS, BAB, FAB, 4 Ps, PASTOR, StoryBrand SB7, each with a worked example and a "use when" table.references/voice-and-headlines.md— the 4 U's, headline families + CTA formula, microcopy, and the Chykalophia voice/banned-phrase rules.
Engagement context
At the start of a task, check for the engagement brief (default ./cro-engagement.md, created by the getting-started skill / /kickoff). If it exists, read it first and write to the client, ICP, price tier, and especially the brand voice/banned-words it records. If it's missing and the work is more than a one-off, offer to capture one via getting-started.
Related skills
Pair with voc-research (the language bank), experiment-design (testing variants), ecommerce-cro-audit (where copy is a lever and persuasion models live), report-information-design (for on-page structure), and outbound-and-positioning (for cold email + the positioning that copy expresses).
Guardrails
Don't invent proof, testimonials, or stats. Don't claim one variant "will win"; say which evidence each draws on. Don't manufacture false urgency. Keep claims substantiated; if you don't have the number, ask for it rather than fabricating.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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