What is customer-reviews?

A command that collects recent customer reviews from review sites, the App Store, and Slack, then saves a weekly summary and drafts a Slack message.

It helps teams track review text, ratings, dates, and recurring customer feedback each week.

It removes the need to gather reviews from several services and summarize them by hand.

How motorway-sandbox/product-os configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to motorway-sandbox/product-os. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/motorway-sandbox/product-os/main/.claude/commands/customer-reviews.md

Clone the repo

git clone --depth 1 https://github.com/motorway-sandbox/product-os

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/motorway-sandbox/product-os/customer-reviews/github.svg)](https://agentmods.dev/commands/motorway-sandbox/product-os/customer-reviews)

Your own site

<a href="https://agentmods.dev/commands/motorway-sandbox/product-os/customer-reviews"><img src="https://agentmods.dev/badge/commands/motorway-sandbox/product-os/customer-reviews/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.

Your own site · 80×15

<a href="https://agentmods.dev/commands/motorway-sandbox/product-os/customer-reviews"><img src="https://agentmods.dev/badge/commands/motorway-sandbox/product-os/customer-reviews.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 955 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00000	$0.00955
Opus 5.5	$0.00000	$0.00382
Sonnet 5.5	$0.00000	$0.00191
Haiku 4.5	$0.00000	$0.00096

Measured 2mo ago against content hash 8a5e24675f26, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

customer-reviews 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 2mo 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.

.claude/commands/customer-reviews.md · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Weekly Customer Reviews Summary

Generate a weekly summary of customer reviews from {your-review-platform}, Google Reviews, and the App Store, then save it and draft a Slack message to {your-pm-channel}.

Instructions

Step 1: Fetch {your-review-platform} reviews

Use WebFetch to pull the most recent reviews from {your-review-platform-url}
Extract: reviewer name, star rating, date, and full review text for every review visible
Note the overall star rating distribution if visible on the page

Step 2: Fetch App Store reviews

Use WebFetch to pull reviews from {your-app-store-url}
Extract: reviewer name, star rating, date, title, and full review text
Only include reviews from the past week

Step 3: Read Slack review channels

Load Slack tools using ToolSearch
Search for channels "reviews" and "app-reviews" using slack_search_channels to get their IDs
Read the past 7 days of messages from both channels using slack_read_channel with appropriate Unix timestamps for oldest/latest
Also search within both channels using slack_search_public with keywords like "star review", "{your-company-name}", "support", "easy", "recommend" to surface reviews where the text content is in the message body (many reviews are posted as rich attachments with empty text fields)
Extract any readable review content from Google Reviews (these tend to have visible text in the #reviews channel)

Step 4: Categorise into themes

From ALL collected reviews across all sources, identify the key themes. For each theme provide:

A descriptive name
An estimated percentage of reviews falling into this category (use the overall {your-review-platform} star distribution to weight positive vs negative)
Whether it is positive or negative sentiment
2-3 direct quotes from actual reviews

Common themes to look for (but don't limit to these):

Positive: Easy/simple process, fair pricing, helpful staff, fast payment, better than alternatives
Negative: Pricing issues, onboarding friction, customer support issues, delivery problems

Read the full file on GitHub · 85 lines

Changes

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.

2mo ago First seen · 85 lines · 0 tokens per session scan A 8a5e24675f26

Subscribe to this mod's changes

customer-reviews is a command published in the GitHub repository motorway-sandbox/product-os (11 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 955 tokens. 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 2026-09-04.

Analytics and metrics Marketing and SEO

customer-reviews next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
customer-reviewsmotorway-sandbox/product-os	Command	11	5mo ago	MIT	A	0	Claude Code
checklistgithub/spec-kit	Command	148k	yesterday	MIT	A	13	Claude Code
clarifygithub/spec-kit	Command	148k	yesterday	MIT	A	27	Claude Code
specifygithub/spec-kit	Command	148k	yesterday	MIT	A	13	Claude Code
analyzegithub/spec-kit	Command	148k	yesterday	MIT	A	26	Claude Code
convergegithub/spec-kit	Command	148k	yesterday	MIT	A	35	Claude Code
implementgithub/spec-kit	Command	148k	yesterday	MIT	A	14	Claude Code

product-os: Command for Claude Code