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 kgelster/awesome-ecom-skills --skill ecom-landing-pagesgit clone --depth 1 https://github.com/kgelster/awesome-ecom-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/kgelster/awesome-ecom-skills/ecom-landing-pages)<a href="https://agentmods.dev/skills/kgelster/awesome-ecom-skills/ecom-landing-pages"><img src="https://agentmods.dev/badge/skills/kgelster/awesome-ecom-skills/ecom-landing-pages/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/kgelster/awesome-ecom-skills/ecom-landing-pages"><img src="https://agentmods.dev/badge/skills/kgelster/awesome-ecom-skills/ecom-landing-pages.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 | $0.00173 | $0.02149 |
| Opus 5 | $0.00086 | $0.01074 |
| Sonnet 5 | $0.00035 | $0.00430 |
| Haiku 4.5 | $0.00017 | $0.00215 |
Grade A, and why
ecom-landing-pages 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 12d 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 — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ecom Landing Pages
Turn a store brief into two deliverables: a ranked list of landing-page
concepts, and a build blueprint for the ones worth shipping. The method was
reverse-engineered from Mill.com, a DTC brand running ~40 production /lp/
pages off a single product. That spread is the whole idea in one sentence:
one product becomes many landing pages by varying the angle, not the
product. A person who clicks a "feed your chickens" ad and a person searching
"nyc curbside compost" want the same device but need different first sentences.
This is the one platform-neutral skill in the collection: landing-page thinking
is the same on any CMS, so the ecom- prefix, not shopify-. Execution notes
that differ by platform are called out where they matter.
When this fires
- A store needs landing-page concepts for paid traffic, a campaign, a new segment, a season, or an event.
- A concept got chosen and needs building into a real page.
- An existing landing page needs an audit against best practice.
Not for full-site IA, PDPs, collection pages, or blog/SEO articles: those live inside the browse flow and compete for attention. A landing page has one goal and strips the chrome. Different rules.
The loop
1. Intake from the live storefront
Read the store's real site: homepage, key product pages, collections, the sitemap if it helps. Never invent products, audiences, or offers: an empty intake field is a signal, not a license to make something up. Pull:
- Product / offer: what sells, price, the single most important thing it does.
- Core value prop: the one-sentence promise.
- Distinct audiences: buyers segmented by identity, not demographics.
- Top pains: the problems that drive purchase, in the customer's own words.
- Use-cases: the different jobs the product does.
- Geos / markets: cities or regions with concentrated demand or local programs.
- Seasonal / event calendar: sale moments, in-person events, launches.
- Offers: trials, guarantees, discounts, bundles, financing.
- Gift / occasion fit: is it giftable? which occasions?
- B2B / segments: institutional buyers with a longer cycle and different criteria.
- Partner / affiliate channels: creators, trade partners, referrers.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 170 lines · 173 tokens per session scan A dd29a8ccff39
ecom-landing-pages is a skill published in the GitHub repository kgelster/awesome-ecom-skills (46 stars, last pushed 20d ago), licensed MIT. It adds 173 tokens to every session and 2,149 once invoked, about $0.0009 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 2026-08-30.
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