# Review Reply Desk: AI-drafted review replies, checked for privacy and offers, approved by the owner

> Let an agent draft your Google and Yelp review replies without the mistakes that cost money. A checker refuses drafts that use a last name or details from your records, offer a discount for a better review, ask for a review to be changed, argue, invent numbers or promises, or repeat your last reply word for word. Health topics, allergies and legal threats go to the owner, clinics get a stricter privacy mode, and nothing is posted until the owner approves it at a real terminal.

- URL: https://paperchasewebb.ai/bots/marketplace/items/review-reply-desk-owner-approved-review-replies-privacy-checker/
- Type: Prompt pack
- Category: Solo business
- By: PaperChaseWebb
- Works with: Claude Code, Codex, Grok Bot, Hermes (named in the listing); Plain Markdown files, a small Python checker, and rules for AGENTS.md and CLAUDE.md, Claude Code and Codex notes, Hermes notes and a Grok Bot standing order. The agent files were checked by the checker on Linux; they were not loaded inside each agent for this release
- Price: $24 USD
- Difficulty: Beginner
- Setup time: 45 min
- Time to result: The worked example in 5 minutes; your own business set up and the eval set passing in under an hour
- Format: Markdown (.md) file, review-reply-desk-owner-approved-review-replies-privacy-checker.md
- Version: 1.0, updated 2026-11-01
- License: Use inside your own business or for your clients' businesses. Do not resell or republish the kit itself.

## What you end up with

Every review gets a specific, human reply on time, and nothing goes public that could break a platform rule, a privacy law or your own policy.

## What you get

- 21 sections and an appendix in one .md file, with a one-line unpack for all 63 files
- review_check.py: 25 reply checks, from last names, record details and public offers to invented numbers, repeated wording and planted instructions in reviews
- A health privacy mode for dental, medical and care practices, with a worked dental example
- A fake-review path: evidence lines and a report for the owner instead of a public argument
- A queue check for one and two star reviews left past your deadline, and replies changed or posted without approval
- The owner step: approve.py needs a real terminal, part of the draft hash and the owner name; agent sessions and piped input are refused and it posts nothing
- A 20-review eval set with expected decisions, rules and two skills for Grok Bot, Claude Code, Codex and Hermes, six prompts, templates and a review-request rules card
- The test harness: 41 unit tests and 169 planted faults you can repeat

## Who it is for

Local businesses and the people who answer their reviews, who want an agent to do the drafting without risking a public mistake.

## Tools needed

- Python 3.8 or newer: runs the reply checker, the queue check, the eval set and the owner approval script; standard library only
- Grok Bot, Claude Code, Codex or Hermes: drafts replies to exported reviews under the AGENTS.md rules or the Grok Bot standing order; never posts and never approves
- Your reviews as a CSV: exported or copied from Google, Yelp or wherever you collect them; the kit never logs in to any platform
- You need: Python 3.8 or newer
- You need: Your reviews, exported or copied into a CSV
- You need: Someone at the business who decides and posts the final reply

Cost to run: The kit is the only purchase. Everything runs locally with Python; the checker makes no network calls and logs in to nothing.

## How it works

1. **Unpack and test.** Save the kit as pack.md in an empty folder, run the unpack line from Appendix A, then sh test_all.sh. Expected: 63 files written; 41 tests OK; 169 of 169 planted faults caught.
2. **Watch the flow.** Run sh example/run_example.sh and read it next to section 16. Expected: A bakery first draft with 10 high findings, the fixed draft clean, a dental draft caught in health mode and a piped approval refused.
3. **Put in your business.** Fill in desk/desk.json and desk/facts.md, then run python3 desk/review_check.py desk. Expected: No findings, or a short list of gaps to fix first.
4. **Give the agent its exam.** Replace the eval reviews with twenty of your own, paste the rules into your agent, have it draft them from scratch and run review_check.py set with --fail-on medium. Expected: Every decision matches and every draft is clean before the agent touches live reviews.

## Sample prompt: Draft the new reviews (Grok Bot, Claude Code, Codex, Hermes)

```
Follow skills/review-reply for every review in queue/reviews.csv with no draft. Never post. Report each draft's decision and finding count.
```

Prompt 1 of 6.

## Sample prompt: Catch repeated wording (Grok Bot, Claude Code, Codex, Hermes)

```
Read the last 20 files in queue/approved. List any opening or closing line used more than twice and add it to banned_phrases in a proposed diff. Do not edit desk.json.
```

Prompt 3 of 6.

## Sample prompt: Fake review note (Grok Bot, Claude Code, Codex, Hermes)

```
Follow skills/fake-review-report for review [id]. Evidence only. Do not reply in public and do not file anything.
```

Prompt 5 of 6.

## Free preview of review-reply-desk-owner-approved-review-replies-privacy-checker.md

````markdown
# Review Reply Desk: AI-drafted review replies, checked for privacy and offers, approved by the owner

Version 1.0, 2026-11-01. By PaperChaseWebb. For owners and agencies who want an AI agent to draft replies to Google, Yelp and other customer reviews without leaking private details, offering something for a better rating, or sounding like the last fifty replies. Works with Grok Bot, Claude Code, Codex and Hermes. Python 3.8 or newer, standard library only, no API keys, no logins. Nothing is ever posted by the kit or the agent. Tested with 41 unit tests and 169 planted faults on Linux with Python 3.13, 3.12, 3.11, 3.9 and 3.8. All business and reviewer data in this kit is made up.

Review replies look like the easiest job to hand to an agent. They are short, public and repetitive. They are also where a small business can get into real trouble in one sentence.

In 2022 a dental practice agreed to pay $23,000 to the US Department of Health and Human Services and take on a two-year corrective plan after its replies to Yelp reviews disclosed patients' names, treatment and insurance details, sometimes giving a full name where the reviewer had used only a nickname. The FTC's rule on consumer reviews, in force since October 2024, covers incentives that depend on what a review says and threats used to get reviews taken down. And people notice when every reply opens with the same line: in a Reddit thread this year, a business owner described a client asking "are you replying with a bo
````

## Test record

- Date: Nov 1, 2026
- What was run: tests/test_check.py (21), test_modes.py (10), test_approve.py (6, on a real pseudo terminal) and test_mini.py (4); tests/mutate.py with 169 planted faults across replies, settings, agent rules, the queue and the eval set, plus 112 against review_mini.py; review_check.py set on the 20-review eval set; example/run_example.sh end to end; and the unpack line with test_all.sh. Linux, Python 3.13, 3.12, 3.11, 3.9 and 3.8.
- Result: 41 passed, 0 failed on all five versions; 169 of 169 and 112 of 112 planted faults caught; 20 of 20 eval drafts clean; the example caught the bakery and dental first drafts and refused piped approval; the unpack line wrote 63 identical files and test_all.sh passed there.
- Not run: A live Grok Bot, Claude Code, Codex or Hermes session. A real business's reviews or a real Google or Yelp account. macOS or Windows. Non-English reviews.

Copied from this item's dated test notes. What was not run stays in.

## Worth knowing

- The agent rules were checked by the checker but not loaded inside a live Grok Bot, Claude Code, Codex or Hermes session for this release. The eval drafts were written by hand to the rules. Give your agent the entrance exam in section 4 before you rely on it.
- The checker works on words, numbers and links. It cannot tell whether a reply built from true facts is still unkind or misleading, and its topic lists are a floor, so the owner reads every draft before it is posted.
- It does not log in to Google, Yelp or any platform and posts nothing. Reviews come in as a CSV and you post approved replies yourself.
- The owner step assumes the agent cannot run approve.py at a terminal. Run it as a separate user; agent rules alone are not a hard boundary.
- Not legal advice. The health mode follows the lesson of a 2022 US settlement over review replies, and the review-request card summarizes the FTC rule and Google policy as of 2026-10-31; check your own rules.
- All businesses and reviews in the kit are made up. English only. Tested on Linux only; macOS and Windows were not tested.
- On 2026-11-01 on Linux: 41 unit tests, 169 of 169 planted faults and 112 of 112 sample faults passed on Python 3.13, 3.12, 3.11, 3.9 and 3.8; 20 of 20 eval drafts clean; the unpack line wrote 63 identical files and test_all.sh passed in that folder.

## Questions

**Which agents does it work with?** Any agent that can read files and run a script. The kit has rules for AGENTS.md and CLAUDE.md, Claude Code and Codex notes, Hermes notes and a Grok Bot standing order. Those were checked by the checker, not loaded in each agent for this release.

**Will it post replies for me?** No. It writes drafts. You approve a draft at a terminal and post it yourself on Google, Yelp or wherever the review is.

**We are a dental or medical practice. Is it safe to use?** It has a health mode that refuses any name and any wording that confirms the reviewer was a patient, and sends care complaints to you. It lowers the risk; it is not legal advice.

**Can I offer an unhappy customer something?** Yes, privately and after you decide. The checker refuses offers in public replies, and never ties anything to a review.

**Can you set it up for us?** Yes. Our Install sprint sets up your facts, rules and agent, or Managed Ops runs it for you each month. Book a call or write to mgmt@paperchasewebb.com.

## How to buy

$24 one time at https://paperchasewebb.ai/bots/marketplace/items/review-reply-desk-owner-approved-review-replies-privacy-checker/. Stripe checkout, then an instant download page; the download link is also in your emailed receipt.

Seller: PaperChaseWebb Inc., mgmt@paperchasewebb.com