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 Affitor/affiliate-skills --skill product-showcase-pagegit clone --depth 1 https://github.com/Affitor/affiliate-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/affitor/affiliate-skills/product-showcase-page)<a href="https://agentmods.dev/skills/affitor/affiliate-skills/product-showcase-page"><img src="https://agentmods.dev/badge/skills/affitor/affiliate-skills/product-showcase-page/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/affitor/affiliate-skills/product-showcase-page"><img src="https://agentmods.dev/badge/skills/affitor/affiliate-skills/product-showcase-page.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 | $0.00110 | $0.03494 |
| Opus 5 | $0.00055 | $0.01747 |
| Sonnet 5 | $0.00022 | $0.00699 |
| Haiku 4.5 | $0.00011 | $0.00349 |
Grade A, and why
product-showcase-page 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- product-showcase-page — 100% identical, 0 lines differ
- product-showcase-page — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 342 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Showcase Page
Build a long-form, single-product showcase page as a self-contained HTML file. Goes deeper than a standard landing page — includes a full hero section, feature breakdown with icons, use case demonstrations, testimonials, a pricing comparison table, FAQ with accordions, and multiple high-intent affiliate CTAs. Designed for pre-sold traffic (readers who came from a review or comparison) and wants to make the final conversion push.
When to Use
- User wants a dedicated page for one product that covers everything a buyer needs to know
- User says "showcase page", "product spotlight", "deep-dive page", "feature breakdown page"
- User wants a page longer than a standard landing page — for high-ticket products needing more persuasion
- User is sending warm traffic (from a blog post or email) and wants to close the sale
- User wants a page that can double as a product review in page form
Workflow
Step 1: Gather Product Data
If product data is available from S1 or prior conversation, use it directly.
Otherwise, use web_search to research the product:
- Features:
"[product name] features"— gather 6-12 distinct capabilities - Pricing:
"[product name] pricing"— all tiers with feature differences - Use cases:
"[product name] use cases"OR"[product name] examples"— concrete applications - Testimonials:
"[product name] reviews"on G2/Capterra — find real sentiment (do not copy verbatim — paraphrase or create realistic representative examples) - Competitors:
"[product name] vs"— 2-3 competitors for the pricing comparison - FAQ:
"[product name] questions"OR check product's own FAQ page
Organize the research into these buckets:
- Core features (6-12, each with a one-sentence benefit statement)
- Use cases (3-5, each framed as a specific problem solved)
- Pricing tiers (2-4 tiers with included features and price)
- Comparison data (the 5-8 dimensions where this product wins vs. competitors)
- Social proof (ratings, user counts, company names using it)
- FAQ answers (6-10 questions)
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 · 342 lines · 110 tokens per session scan A 35f8c002e685
product-showcase-page is a skill published in the GitHub repository Affitor/affiliate-skills (658 stars, last pushed 6d ago), licensed MIT. It adds 110 tokens to every session and 3,494 once invoked, about $0.0006 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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