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 lhitches/claude-seo-skills --skill review-proof-sortergit clone --depth 1 https://github.com/lhitches/claude-seo-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/lhitches/claude-seo-skills/review-proof-sorter)<a href="https://agentmods.dev/skills/lhitches/claude-seo-skills/review-proof-sorter"><img src="https://agentmods.dev/badge/skills/lhitches/claude-seo-skills/review-proof-sorter/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/lhitches/claude-seo-skills/review-proof-sorter"><img src="https://agentmods.dev/badge/skills/lhitches/claude-seo-skills/review-proof-sorter.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 | $0.00199 | $0.01623 |
| Opus 5.5 | $0.00080 | $0.00649 |
| Sonnet 5.5 | $0.00040 | $0.00325 |
| Haiku 4.5 | $0.00020 | $0.00162 |
Grade A, and why
review-proof-sorter 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 today.
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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Proof Sorter: Google reviews into proof on every service page
Most businesses have their best proof sitting on a Google Business Profile, and a service page with none. A review about fixing someone's hot water belongs on the hot water page, because that's the job the visitor on that page needs done. This skill sorts the reviews and hands back a block of proof for each page, ready to paste.
Keep it practical. The deliverable is one proof block per page the owner can add this week.
Bundled resources
scripts/review_proof_sorter.py: sorts reviews by service and place with a keyword first pass, picks whole-sentence quotes, lists the words customers repeat, writes the outputs. Stdlib only, no network.assets/services-template.csvandassets/places-template.csv: the two input layouts.
Step 1: Get the inputs (don't guess)
If ./business-context.md exists, read it first and confirm rather than re-ask.
- The reviews. Any of these works:
- Pasted straight into the chat. Save them to
reviews.txt, one review per block with a blank line between (keep the reviewer name, date and stars on the first line if they pasted them). - An export or a reviews-widget download as CSV or JSON. The script reads columns called text/review/comment, name/author, date, rating/stars and place/location.
- If the business has several Google profiles (several branches), keep which profile each
review came from in a
placecolumn. Never make up, edit or "tidy" a review. If the user can't get their reviews out, stop and tell them how: open the Business Profile, copy the reviews, paste them here.
- Pasted straight into the chat. Save them to
- The service pages. The URL and name of each service page. Offer to read the site's menu or sitemap to list them, then confirm the list with the user.
- The places (optional). Suburbs, towns or cities they serve, and the location page for each if they have one.
Step 2: Write the keyword lists (you do this, the user checks)
For each service, write the words a customer would use in a review, not the business's own
jargon. A plumber's "hot water system replacement" page gets: hot water; hot water system;
water heater; no hot water; heat pump; instantaneous. Save as services.csv (layout in
assets/services-template.csv, keywords separated by ;). Add suburb aliases to places.csv
(e.g. "St Kilda; St Kilda East").
What ships with it
5 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.
- today First seen · 107 lines · 199 tokens per session scan A 9d7bfc69f549
review-proof-sorter is a skill published in the GitHub repository lhitches/claude-seo-skills (21 stars, last pushed yesterday), licensed MIT. It adds 199 tokens to every session and 1,623 once invoked, about $0.0008 per session on Opus 5.5. 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 2026-10-27.
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