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 surfmind-space/awesome-surfmind --skill product-review-summarizergit clone --depth 1 https://github.com/surfmind-space/awesome-surfmindWrote 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/surfmind-space/awesome-surfmind/product-review-summarizer)<a href="https://agentmods.dev/skills/surfmind-space/awesome-surfmind/product-review-summarizer"><img src="https://agentmods.dev/badge/skills/surfmind-space/awesome-surfmind/product-review-summarizer/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/surfmind-space/awesome-surfmind/product-review-summarizer"><img src="https://agentmods.dev/badge/skills/surfmind-space/awesome-surfmind/product-review-summarizer.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 | $0.00064 | $0.00541 |
| Opus 5 | $0.00032 | $0.00270 |
| Sonnet 5 | $0.00013 | $0.00108 |
| Haiku 4.5 | $0.00006 | $0.00054 |
Grade A, and why
product-review-summarizer 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 11d 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Summarizer
Condense a pile of reviews into the patterns that matter for a buying decision — recurring pros and cons, reliability issues, who it fits, and the red flags that show up again and again. Work only from the reviews actually present, and don't treat one dramatic review as the verdict.
- Identify repeated positive and negative themes instead of over-weighting single dramatic reviews.
- Note review recency, product versions, verified-purchase hints, and possible review manipulation when visible.
- Call out reliability, quality control, support, delivery, sizing, compatibility, or safety issues when they recur.
- Translate vague sentiment into practical buyer-fit guidance, and flag what to check before buying.
If fewer than ~5 reviews are available, note the small sample size prominently and caveat every pattern claim. Return concise headings and include these sections when they fit: Overall pattern, Pros, Cons, Repeated red flags, Best-fit buyer, Questions before buying. Don't invent statistics that aren't visible; if the context is insufficient, say what's missing and give the best supported next step.
Example
Reviews (selected text from a product page):
"Battery died after 3 months." · "Great sound but the app keeps disconnecting." · "Comfortable for small ears." · "Stopped charging in week 6 — second pair with the same issue." · "Love them, perfect for the gym."
Summary:
Overall pattern: Well-liked sound and fit, but a recurring hardware-reliability problem (battery/charging failures within weeks) shows up across multiple reviewers.
Pros
- Sound quality and comfort praised repeatedly; works well for workouts and smaller ears.
Cons
- Companion app disconnects mid-use.
Repeated red flags
- Two separate reviewers report charging/battery failure within 3–6 weeks — a pattern, not a one-off.
Best-fit buyer: Someone who wants comfortable gym earbuds and values sound over long-term durability.
Questions before buying: What's the warranty and return window? Are the charging complaints addressed in a newer firmware or hardware revision?
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.
- 11d ago First seen · 48 lines · 64 tokens per session scan A 2ffe07039fa9
product-review-summarizer is a skill published in the GitHub repository surfmind-space/awesome-surfmind (5 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 541 once invoked, about $0.0003 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 2026-08-31.
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