Borrowing it
Nothing to install: this file belongs to harukiseller-droid/commerce-agent-bench. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/harukiseller-droid/commerce-agent-bench/main/.agents/skills/product-page-audit/SKILL.mdgit clone --depth 1 https://github.com/harukiseller-droid/commerce-agent-benchWrote 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/harukiseller-droid/commerce-agent-bench/product-page-audit)<a href="https://agentmods.dev/skills/harukiseller-droid/commerce-agent-bench/product-page-audit"><img src="https://agentmods.dev/badge/skills/harukiseller-droid/commerce-agent-bench/product-page-audit/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/harukiseller-droid/commerce-agent-bench/product-page-audit"><img src="https://agentmods.dev/badge/skills/harukiseller-droid/commerce-agent-bench/product-page-audit.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 | $0.00020 | $0.00297 |
| Opus 5 | $0.00010 | $0.00148 |
| Sonnet 5 | $0.00004 | $0.00059 |
| Haiku 4.5 | $0.00002 | $0.00030 |
Grade A, and why
product-page-audit 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.
What it actually says
Product Page Audit
Purpose
Review product-page correctness and buyer-risk regressions using repository and runtime evidence.
When to use
Use when reviewing a product template, product-page implementation, or buyer-facing product detail surface.
Inputs
- product-page source, template, or fixture;
- runtime data source if one is available;
- visible page or test evidence for buyer-facing behavior.
Required checks
- Identify runtime sources for title, price, variants, inventory, images, and product metadata.
- Check primary heading, image alt text, add-to-cart control, variant state, price/availability consistency, and mobile-safe markup.
- Check whether shipping/returns/specifications are verified data or generic hard-coded claims.
- Check Product structured data against visible/runtime facts.
- Mark unavailable merchant facts
UNKNOWN.
Output contract
Use the finding contract from PROTOCOL.md. Never convert a plausible product detail into a fact.
Failure conditions
- Missing runtime or verified merchant data means the affected claim is
UNKNOWN. - Do not certify checkout, inventory, price, shipping, or returns behavior from static markup alone.
- Do not report a schema value as valid when it is not visible or runtime-backed.
Verification
Run focused tests/evals, inspect the rendered route when available, and identify any unverified browser or platform behavior.
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 · 41 lines · 20 tokens per session scan A 6700d139c907
product-page-audit is a skill published in the GitHub repository harukiseller-droid/commerce-agent-bench (102 stars, last pushed 1mo ago), licensed MIT. It adds 20 tokens to every session and 297 once invoked, about $0.0001 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.
Other skills, from other repositories
amazon-reviews-api-skill
This skill helps users automatically extract Amazon product reviews via the Amazon Reviews API. Agent should proactively apply this skill when users express needs like getting reviews for Amazon product with ASIN B07TS6R1SF, analyzing customer feedback for a specific Amazon item, getting ratings and comments for a…
amazon-competitor-analyzer
Scrapes Amazon product data from ASINs using browseract.com automation API and performs surgical competitive analysis. Compares specifications, pricing, review quality, and visual strategies to identify competitor moats and vulnerabilities.
asc-subscription-localization
Bulk-localize subscription, subscription-group, and in-app purchase display names across App Store locales using asc, including API 4.4.1 version-scoped v2 resources. Use when filling or updating subscription/IAP names and descriptions without App Store Connect UI work.
food-order
Reorder previous Foodora orders, preview cart contents, and track delivery ETA/status with ordercli. Use when the user wants to reorder food, check delivery status, or browse recent Foodora order history. Never confirm an order without explicit user approval.
product-description-generator
E-commerce product description generator for any platform. Generates optimized titles, bullet points, descriptions, and backend keywords using competitor research + keyword scoring + FABE copywriting. Two modes: (A) Create — generate listing from product specs with optional competitor analysis, (B) Optimize — improve…
amazon-price-tracker
Amazon price monitoring and competitive pricing intelligence. Real-time price tracking, Buy Box analysis, promotion detection, and dynamic pricing strategy optimization. Use when the user asks about price monitoring, competitor pricing, Buy Box tracking, or pricing strategy.