Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add swan-gtm/gtm-skills --skill ad-copywritinggit clone --depth 1 https://github.com/swan-gtm/gtm-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/swan-gtm/gtm-skills/ad-copywriting)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/ad-copywriting"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/ad-copywriting/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/ad-copywriting"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/ad-copywriting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.03624 |
| Opus 5 | $0.00016 | $0.01812 |
| Sonnet 5 | $0.00006 | $0.00725 |
| Haiku 4.5 | $0.00003 | $0.00362 |
Grade A, and why
ad-copywriting scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ad Copywriting - Headline Formulas, Visual Design & Voice of Customer
How to actually write the copy: headline formulas, visual design principles, and the process for gathering real customer language before writing anything. Applies to LinkedIn and Meta ads.
Rule #1: Write From the Customer's Mouth, Not the Product's Marketing
The single biggest mistake in ad copywriting is writing from the brand's marketing language instead of the customer's actual words.
What this looks like in practice:
- Brand voice: "Real-time visibility across all business units" (product marketing)
- Customer voice: "I used to spend 6-8 hours a week on reporting. Now it takes 15 minutes." (how they actually talk)
The brand voice describes features. The customer voice describes the transformation in their daily life. The customer voice wins every time because it mirrors what the ICP is thinking and feeling.
The rule: Before writing a single line of ad copy, gather voice-of-customer data. Use their words, not yours.
Voice of Customer: Where to Get It
Gather real language from these sources before writing ad copy. Ranked by quality:
Tier 1: Direct Customer Language
- G2/Capterra/TrustRadius reviews - real users describing problems and outcomes in their own words. Look for the "before" state (what was painful) and "after" state (what changed).
- Sales call transcripts / discovery call notes - how prospects describe their problem before they know the solution. This is gold because it's unfiltered.
- Customer testimonials / case studies on the website - curated but still in customer language. Look for specific numbers and outcomes.
- Support tickets / onboarding feedback - how users describe confusion or value in real-time.
Tier 2: ICP Language in the Wild
- Reddit threads where the ICP discusses the problem (e.g., relevant subreddits for your category)
- LinkedIn posts from ICP personas complaining about or discussing the problem
- Conference talks / webinar transcripts where ICP personas discuss challenges
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 330 lines · 32 tokens per session scan A 41cc91dab55e
ad-copywriting is a skill published in the GitHub repository swan-gtm/gtm-skills (153 stars, last pushed 2d ago), licensed MIT. It adds 32 tokens to every session and 3,624 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
ad-campaign-analyzer
Analyze cross-channel campaign data, quantify uncertainty, and propose evidence-labeled budget tests without overstating causality.
google-search-ads-builder
End-to-end Google Search Ads campaign builder. Performs deep keyword research (competitor SEO, review language mining, Reddit/HN community terminology, site audit), builds keyword architecture with funnel mapping and intent classification, creates ad group structure, generates headline/description variants, builds…
meta-ads-analyzer
Diagnose Meta Ads campaign performance and account gaps using Meta's actual system mechanics — including customer-journey coverage, Breakdown Effect, Learning Phase, Auction Overlap, Pacing, and Creative Fatigue. Use for performance diagnosis, account audits, full-funnel or TOF/MOF/BOF gap analysis, deciding what to…
ad-campaign-analyzer
Analyze ad campaign performance data (Google, Meta, LinkedIn) to identify what's working, what's wasting budget, and specific cut/scale/test recommendations. Runs statistical analysis, funnel diagnostics, and multi-channel budget reallocation with specific dollar-amount shift recommendations and scenario modeling.
competitor-ad-intelligence
Scrape competitor ads from Meta, TikTok, Google, and LinkedIn ad libraries, analyze creative patterns (hooks, formats, CTAs), reverse-engineer landing page funnels, and produce a strategic teardown with vulnerability analysis and counter-play recommendations. Use when you need to understand the competitive ad…
ad-angle-miner
Mine the highest-converting ad angles from customer reviews, Reddit complaints, support tickets, and competitor ads. Extracts actual pain language, competitor weaknesses, and outcome phrases that real buyers use. Outputs a ranked angle bank with proof quotes and recommended ad formats per angle.