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 finsilabs/awesome-ecommerce-skills --skill product-reviews-ratingsgit clone --depth 1 https://github.com/finsilabs/awesome-ecommerce-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/finsilabs/awesome-ecommerce-skills/product-reviews-ratings)<a href="https://agentmods.dev/skills/finsilabs/awesome-ecommerce-skills/product-reviews-ratings"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/product-reviews-ratings/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/finsilabs/awesome-ecommerce-skills/product-reviews-ratings"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/product-reviews-ratings.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00029 | $0.03071 |
| Opus 5 | $0.00015 | $0.01536 |
| Sonnet 5 | $0.00006 | $0.00614 |
| Haiku 4.5 | $0.00003 | $0.00307 |
Grade A, and why
product-reviews-ratings 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 — 284 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Reviews & Ratings
Overview
Product reviews are the strongest social proof signal in e-commerce — products with 5+ reviews convert at 270% higher rates than products with none. Every major platform has review apps that handle collection, moderation, schema.org markup for Google star ratings, and verified purchase badging without custom code. Only build a custom review system if you need proprietary moderation logic, deep API integration, or review data in your own database.
When to Use This Skill
- When launching a new store and needing a review collection and display system
- When implementing schema.org
AggregateRatingmarkup to enable star ratings in Google Search results - When building a moderation workflow to prevent fake or spam reviews
- When displaying verified purchase badges to increase review credibility
- When triggering post-purchase review request emails automatically after delivery
- When importing reviews from one platform or app to another
Core Instructions
Step 1: Determine platform and choose the right review tool
| Platform | Recommended Tool | Why |
|---|---|---|
| Shopify | Judge.me | Free plan includes unlimited reviews, photo reviews, verified purchase badges, schema.org markup, and post-purchase email requests |
| Shopify | Yotpo | More advanced features: Q&A, loyalty integration, Google Shopping reviews syndication — best for mid-market+ stores |
| WooCommerce | WooCommerce built-in reviews + WP Product Review plugin | WooCommerce has built-in star ratings; add WP Product Review for schema.org markup and verified purchase gating |
| WooCommerce | Judge.me for WooCommerce | Same feature set as the Shopify version; available as a WooCommerce integration |
| BigCommerce | Judge.me or Yotpo | Both available on the BigCommerce App Marketplace with full feature parity |
| Custom / Headless | Build review API | Required when reviews need to live in your own database with custom moderation logic |
What ships with it
7 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.
- evals/bayesian-rating-calculation-and-schema-o/criteria.json 2.6 KB
- evals/bayesian-rating-calculation-and-schema-o/task.md 1.9 KB
- evals/review-display-helpful-votes-and-admin-m/criteria.json 2.7 KB
- evals/review-display-helpful-votes-and-admin-m/task.md 2.0 KB
- evals/review-submission-endpoint-with-auto-mod/criteria.json 3.1 KB
- evals/review-submission-endpoint-with-auto-mod/task.md 1.8 KB
- tile.json 237 B
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 · 284 lines · 29 tokens per session scan A 46006c2eb1af
product-reviews-ratings is a skill published in the GitHub repository finsilabs/awesome-ecommerce-skills (52 stars, last pushed 6mo ago), licensed MIT. It adds 29 tokens to every session and 3,071 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.
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