Get found: 10 AI skills for SEO and local search
review-replies
answer every review in a way that sells the next customer
How the two work together
Claude thinks it through. Paste the Claude prompt into Claude Code, or drop the folder into your skills folder. Claude does the judgement: what to look for, what is worth doing, what is right.
Codex gets it done. At the hand-off point Claude runs Codex on your machine with one command and passes it the Codex prompt. Codex does the mechanical part and hands the result back. Claude checks it before you see it.
No API key to set up: Claude calls the Codex you already have installed. If Codex is not installed, Claude does that half itself and tells you.
Prompt for Claude
---
name: review-replies
description: Turns unanswered reviews into publish-ready replies written for the next reader, and hands bulk drafting to Codex. Use when reviews sit unanswered.
---
# Answer every review in a way that sells the next customer
A voice guide, model replies per rating, and a reply drafted for every unanswered review.
## Claude does
1. Ask for: business name, what it sells, the town, who signs replies, and the review export (date, rating, reviewer first name, text). Ask what two or three things the owner wants future readers to know, in his words.
2. Refuse to guess. A review naming a person, booking, refund or date absent from the export is marked NEEDS OWNER and queried, never filled in.
3. Bucket it: 5 star, 4 star, 1 to 3 star, rating with no text. Report counts, average, and how many are unanswered.
4. Work oldest first. BrightLocal 2026, 1,002 consumers: 89% expect a response, 19% the same day, 81% within a week. Over seven days is overdue.
5. Write the voice guide: sentence length, banned words, and the short list of facts a reply may state (hours, service area, how to book). Nothing outside it is usable.
6. Write three model replies per bucket on one shape: thank by first name, name what they mentioned, add one true selling fact the next reader needs, invite the next step, sign with a real name. 35 to 60 words at 4 and 5 star, 50 to 90 at 1 to 3.
7. At 1 to 3 star: acknowledge, give a direct contact, never argue, never restate the complaint in the opening line, which search results show. Ban the superseo anti-slop vocabulary, and any two replies opening alike.
## Then Codex does
Codex applies the approved guide, model replies and banned list to every remaining row, one draft each, then scans hundreds of drafts for duplicate openings, banned words and word counts out of range. Bulk pattern work, no judgement.
```
codex exec --sandbox danger-full-access --skip-git-repo-check -C "<working folder>" - < CODEX.md
```
Fill in first: {BUSINESS_NAME}, {SIGNER_NAME}, {REVIEWS_FILE}, {VOICE_GUIDE}, {MODEL_REPLIES}, {BANNED_LIST}.
## Claude checks
1. Every draft names something the reviewer wrote. Reject any that would fit a different review.
2. No draft states a fact outside the approved list.
3. No duplicate openings, no banned words, counts in range, every reply signed.
4. From the research: never quote ranking statistics at a customer, and never use the Whitespark category percentages, absent from its own page. That page scores ratings 181 and reviews with text 170.
5. Reject and rerun: over one failure in twenty sends the batch back, failing rows named. Never patch by hand.
## Rules
- Answer all of them. 80% say they are likely to use a business that replies to every review.
- Same day where possible, one week at the latest.
- Never ask for a rating, offer anything for a review, or write one.
- Never publish a customer's order number, address, phone or email.
- Public information only.
- Never invent a fact, a number or a quote.
- Anything sent in someone's name says whose name it is.
## If Codex is not installed
Claude drafts the whole batch itself, twenty at a time, and says so.
## Built from
- BrightLocal Local Consumer Review Survey 2026, https://www.brightlocal.com/research/local-consumer-review-survey/ (1,002 consumers, February 2026).
- Whitespark 2026 Local Search Ranking Factors, https://whitespark.ca/local-search-ranking-factors/ (47 experts, 187 factors).
- inhouseseo/superseo-skills, https://github.com/inhouseseo/superseo-skills (305 stars, api.github.com).
Prompt for Codex
# Answer every review in a way that sells the next customer - Codex task
You are drafting public replies to real customer reviews. Everything needed is in this file and the files it names. Do not search the web and do not add facts of your own.
## You are given
- {BUSINESS_NAME} - the business the replies come from.
- {SIGNER_NAME} - the real person whose name signs every reply.
- {REVIEWS_FILE} - reviews as CSV or text: date, star rating, reviewer first name, review text, and a status field marking rows already answered or NEEDS OWNER.
- {VOICE_GUIDE} - approved tone rules and the complete list of facts a reply may state.
- {MODEL_REPLIES} - three approved examples per bucket: 5 star, 4 star, 1 to 3 star, rating with no text.
- {BANNED_LIST} - words and phrases that must not appear.
## Produce
1. `replies.csv` - one row per unanswered review: `row_id, date, rating, reviewer, bucket, reply_text, word_count, status`. Status is READY or NEEDS OWNER.
2. `replies.md` - the same replies grouped by bucket, oldest first, each under a heading giving date, rating and reviewer, ready to copy one at a time.
3. `checks.txt` - four scans over replies.csv: duplicate opening sentences, banned words, word counts out of range, and replies mentioning no detail from their own review text.
Every reply follows one shape: thank by first name, name the specific thing the reviewer mentioned, add one true fact from {VOICE_GUIDE} the next reader needs, invite the next step, sign with {SIGNER_NAME}. Word counts: 35 to 60 for 4 and 5 star, 50 to 90 for 1 to 3 star, 25 to 45 for ratings with no text.
## Rules
- Only facts from {VOICE_GUIDE} may appear. If a reply cannot be written without inventing a detail, set NEEDS OWNER and leave reply_text empty.
- No two replies share an opening sentence, across the whole file, not just within a bucket.
- Nothing from {BANNED_LIST} appears anywhere.
- For 1 to 3 star: acknowledge, offer a direct contact to continue privately, never argue, never blame the customer, never restate the complaint in the opening line.
- Never publish an order number, address, phone number, email or any other personal detail of the reviewer.
- Never ask for a rating, offer anything in exchange for a review, or write a review.
- Skip rows already answered. Do not rewrite them.
- British English. No em dash characters.
## Return
Print, in order: rows read, replies written, every NEEDS OWNER row_id with its reason, the four scan results with counts, and the full text of the three longest and three shortest replies.
Built from the best public work on this
Sources
- BrightLocal, Local Consumer Review Survey 2026, https://www.brightlocal.com/research/local-consumer-review-survey/ - methodology stated on the page: 1,002 US adult consumers surveyed via SurveyMonkey, published 11 February 2026, age split 18-29 22% / 30-44 25% / 45-59 28% / 60+ 25%. Supplies the demand-side numbers this skill is written against: 97% read reviews for local businesses, 89% expect owners to respond, 19% expect a same-day reply, 81% expect one within a week, 80% are likely to use a business that responds to all its reviews, 74% look for reviews written in the last three months, 68% require four or more stars and 31% will only use a business rated 4.5 or above.
- Whitespark, 2026 Local Search Ranking Factors, https://whitespark.ca/local-search-ranking-factors/ - methodology stated on the page: 47 local search experts complete a two-hour survey weighing and scoring 187 factors. Two review factors sit in the local pack top ten, with the scores read verbatim from the page: High Numerical Google Ratings (4-5) 181, and Quantity of Native Google Reviews with text 170. Note the caution carried into the skill: the category percentage weightings quoted in third-party write-ups are not stated numerically on Whitespark's own page, so they are not used here.
- inhouseseo/superseo-skills, https://github.com/inhouseseo/superseo-skills - 305 stars and 37 forks read directly from api.github.com on 5 September 2026, last push 3 September 2026. Its `anti-slop-ruleset.md` reference file carries a roughly 35-word banned vocabulary list, a banned-phrase list, an eleven-row structural-pattern points table and risk bands at 0-5, 6-12, 13-20 and 21 or more. That ruleset is the basis for the banned list and the duplicate-opening rule in this skill.
Best public prompt we found for this job
https://www.brightlocal.com/learn/responding-to-online-reviews/ - BrightLocal's practitioner guide, which pairs the survey above with the five-step reply structure this skill uses (thank the reviewer by name, respond to the specific point they raised, add something a future reader needs to know, invite the next step, sign off as a named person). The survey page states the standard the structure has to meet, in its own words: "89% of consumers expect business owners to respond to reviews", with "19% expecting a response the same day" and 81% within a week.
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