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review-reputationPurpose, usage and source

Watches what customers are saying in public and in private, then does something about it. Aggregates Google, Yelp, and Facebook reviews alongside disputes, tickets, and email into themes backed by verbatim quotes; drafts a reply to every review in the owner's own voice for approval; spots customers who have gone quiet or look likely to leave; and drafts win-back offers for the ones worth keeping. With Shopify connected, order and fulfillment patterns become a sentiment signal too. Works from pasted or exported reviews when nothing is connected. Use this whenever the owner asks about reviews, ratings, reputation, complaints, or repeat business — including "what are people saying about us," "did we get any bad reviews," "how do I respond to this one-star," "our rating dropped," "which customers have gone quiet," "who hasn't ordered in a while," "how do I win them back," or "are customers happy."

Source retrieved:

Source repository
anthropics/knowledge-work-plugins
SKILL.md
small-business/skills/review-reputation/SKILL.md
Repository stars
34,049
Repository updated
2026-10-30
Categories
Business
Last collected

License: Apache-2.0

Source SKILL.md

Workflow excerpts are reading aids, not executable instructions from Codez. No third-party Skill was run to produce this page.

The purpose and workflow passages below are upstream material, organized and translated for reading. They are distinct from the separately labeled Codez editorial analysis.

What this Skill does

Watches what customers are saying in public and in private, then does something about it. Aggregates Google, Yelp, and Facebook reviews alongside disputes, tickets, and email into themes backed by verbatim quotes; drafts a reply to every review in the owner's own voice for approval; spots customers who have gone quiet or look likely to leave; and drafts win-back offers for the ones worth keeping. With Shopify connected, order and fulfillment patterns become a sentiment signal too. Works from pasted or exported reviews when nothing is connected. Use this whenever the owner asks about reviews, ratings, reputation, complaints, or repeat business — including "what are people saying about us," "did we get any bad reviews," "how do I respond to this one-star," "our rating dropped," "which customers have gone quiet," "who hasn't ordered in a while," "how do I win them back," or "are customers happy."

How the upstream workflow works

Step 1 — Set the window and gather everything

Default to the last 90 days. Reviews move slowly, and a 30-day window on a business with six reviews a quarter produces a report with nothing in it. Read reference/sources.md for the query detail and the fallbacks. Pull in one pass: Public reviews — Google, Yelp, Facebook, and industry sites. Fetch what is visible on the web when no connector reads them, and accept a pasted or exported file whenever the owner has one. Exports are the better source: they carry dates and ratings the page may not. Email — threads carrying complaint or praise language.

Upstream passage · L26 ↗

Step 2 — Extract themes with the customer's own words

Group the evidence into three to five recurring themes. Each theme carries a one-line label, a signal count, and two or three verbatim quotes tagged to their source. Quote verbatim, always. Paraphrase is where this report loses its credibility — the owner needs to see what the customer actually wrote, not a summary of the mood. "Ordered two weeks ago and still nothing" lands. "Customers expressed shipping concerns" does not. Rank by signal count, not by how loud any single complaint was.

Upstream passage · L39 ↗

Step 3 — Read the order data as sentiment

With Shopify connected, behavior often says more than words. Read reference/churn-signals.md for thresholds. Late fulfillment, partial shipments, and repeat refunds against the same product or the same time window usually show up in reviews a few weeks later. Finding the pattern in the orders first is the only chance the owner gets to fix it before it becomes public. Report what the data shows, never what it implies about a number you do not have. If refund reasons are not recorded, say they are unavailable rather than guessing at causes.

Upstream passage · L47 ↗

Requirements and setup

No short requirements passage was selected from this file. This does not mean the Skill has no dependencies. Check the repository setup instructions and referenced files.

Limits and quality checks

No separate limits passage was selected from this file. This does not mean the Skill is safe for every input or environment. Review the complete source and validate your own result.

Start with a safe trial

  1. Check the supported host and the repository installation instructions. Keep the Skill directory and its referenced scripts, assets and documentation together; SKILL.md alone may omit dependencies.
  2. Give the agent your real input, desired output and acceptance criteria. Invocation syntax and available tools depend on the host; this site does not assume a universal install command.
  3. Try the source workflow in a disposable project or on a copy. Review operations that change files, remote services or billable resources before allowing them.
  4. Validate the output against the source quality checks and your own requirements. A successful trigger or a high repository Star count does not establish a correct result.

Skill format and directory specification ↗

Read further in the source

Translation and scope

This reading guide selects passages from the pinned upstream SKILL.md. Translation is assisted. It is not a complete manual or a claim of tested compatibility. Read the original and its referenced files before use.

This introduction refers to the pinned version below; current repository activity and collection time are shown separately.

Source retrieved
Source commit
2574e29377c7173d0cecffef29a6ecbd7f8ccb5d
Source SHA-256
5994e6bf2cd7d80b99fb6ddeee149a3a7ec4cec8b4d5c40acfcabd166e578809
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