Agent skill

Review Management

by ericrisco in ericrisco/rsc-harness

A skill your agent uses when a public review needs an on-voice reply, when you need to earn more reviews legally, or when an aggregate rating is slipping across Google Business Profile, Trustpilot…

MITAuto-check passedSales & Support

Install Review Management

skills CLI
$ npx skills add ericrisco/rsc-harness --skill review-management -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ericrisco/rsc-harness review-management --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ericrisco/rsc-harness.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/review-management .claude/skills/review-management && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
review-management
GitHub stars
174
Token cost
~2.9k tokens
SKILL.md length
1,360 words
Files
5 (incl. scripts, references)
Skills in repo
233
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when a public review needs an on-voice reply, when you need to earn more reviews legally, or when an aggregate rating is slipping across Google Business Profile, Trustpilot…

  • Works in 4 steps: No fake or insider reviews. Don't write,… → No review gating (suppression). You may… → No incentivizing a particular sentiment.… → …
  • A public review needs an on-voice reply
  • SKILL.md covers What this owns vs route…, The legal floor — read before…, Earn reviews cleanly and Respond — the playbook, plus 6 more sections
  • Runs Shell scripts from its folder; reaches googleapis.com

What it does

Review Management is an agent skill from ericrisco/rsc-harness. Use when a public review needs an on-voice reply, when you need to earn more reviews legally, or when an aggregate rating is slipping across Google Business Profile, Trustpilot, the App Store or Google Play — including deciding reply versus flag, getting an unfair one-star removed rather than merely answered, and wiring programmatic replies. NOT a private support ticket against an SLA (that is customer-support), NOT churn, NPS or save plays (that is retention).

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `evals/README.md`, `evals/cases.yaml` and `references/platform-apis.md`).

It sits in Sales & Support, covering Customer support, Customer feedback analysis and Local SEO. The repository describes itself as: Your agent invents things because it has no memory, and can't touch your database because it has no arms. rsc is the meta-harness that gives it both, plus the trade to know the… The licence is MIT.

When your agent uses it

  • A public review needs an on-voice reply
  • You need to earn more reviews legally
  • An aggregate rating is slipping across Google Business Profile
  • Google Play — including deciding reply versus flag

Example prompts

  • “/review-management”

Requirements

  • A Bash shell

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. No fake or insider reviews. Don't write, buy, or solicit reviews from people who
  2. No review gating (suppression). You may not screen for sentiment before the
  3. No incentivizing a particular sentiment. You may offer an incentive to review
  4. No misrepresenting that reviews are independent when they're insider/company-controlled.

What it can do on your machine

Read from SKILL.md and the folder at commit e3d5b33. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Shell), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • googleapis.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Review Management loads about 2.9k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 122 tokens; SKILL.md has 1,360 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~122
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from ericrisco/rsc-harness at commit e3d5b33, republished under its MIT licence (© ericrisco). 1,360 words, ~2,853 tokens.

Download SKILL.mdSave it as .claude/skills/review-management/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
review-management
description
Use when a public review needs an on-voice reply, when you need to earn more reviews legally, or when an aggregate rating is slipping across Google Business Profile, Trustpilot, the App Store or Google Play — including deciding reply versus flag, getting an unfair one-star removed rather than merely answered, and wiring programmatic replies. NOT a private support ticket against an SLA (that is `customer-support`), NOT churn, NPS or save plays (that is `retention`).
tags
reviews, reputation, google-business-profile, trustpilot, ftc, responses, app-store
recommends
customer-support, retention, seo-geo, brand-voice, social-publisher
origin
risco

review-management

You run public reputation as a program. A review is the one customer message every future prospect also reads, so it rolls up into an aggregate that moves local rank and the buy decision. Your job is three artifacts: a review-request flow (earn more, the legal way), a response playbook (reply on-voice, within the SLA, to every rating), and a reputation scorecard (the aggregate signal across surfaces).

You do not write the brand's voice — you consume it. You do not run the private inbox. You do not make the page rank. You own what is public and what it averages to.

What this owns vs route elsewhere

The dividing line is one question: can a stranger read it? If your reply is visible to every future prospect, it's a review — yours. If it's a private channel, it's not.

The askRoute toWhy
Private email/chat/ticket against an SLA../customer-support/SKILL.md1:1, non-public, macro library + queue — not a public reply
Churn risk, NPS, save plays, win-back../retention/SKILL.mdA bad review may signal churn; the save play lives there
Make the profile rank (schema, GEO, local pack beyond reviews)../seo-geo/SKILL.mdReviews feed rank, but on-page/schema is a different lever
Repurpose a 5-star into a social post../social-publisher/SKILL.mdScheduling/cadence of the post, not the review reply

The reply voice — traits, word bank, tone matrix — comes from ../brand-voice/SKILL.md. This skill applies that guide; it never authors it.

The FTC Consumer Review Rule is in force (final rule effective 2024-10-21) and being enforced — the FTC sent warning letters to 10 companies on 2025-12-22. Penalties run up to $53,088 per violation (per the FTC 2025-12 warning letters / press release, the inflation-adjusted figure in force from Jan 2025). Four moves are banned. Internalize them before you draft a single request:

  1. No fake or insider reviews. Don't write, buy, or solicit reviews from people who didn't transact. Why: they're deceptive on their face and the per-violation fine is ruinous.
  2. No review gating (suppression). You may not screen for sentiment before the ask — no "rate us 1–5, and only the happy ones get routed to Google." Routing unhappy customers to a private form while sending happy ones to the public link is illegal suppression. Why: it manufactures a rating that doesn't reflect reality — the exact harm the rule targets.
  3. No incentivizing a particular sentiment. You may offer an incentive to review (if disclosed) — you may not condition it on the review being positive. Why: "$10 for a 5-star" buys sentiment, not feedback.
  4. No misrepresenting that reviews are independent when they're insider/company-controlled.

The one rule that resolves 90% of cases: you may ask everyone; you may not condition the ask, the routing, or the reward on how they feel.

text
Bad  (gating — illegal):  "Loved us? Leave a 5-star here →. Had a problem? Email us instead."
Good (neutral — clean):   "Thanks for choosing us. Share your honest experience here → [link]."

Earn reviews cleanly

Ask within 24–48h of the transaction — peak emotional recency. Pick the channel by context; a hybrid SMS-then-email (48–72h gap) lifts total collection 40–60%.

ChannelUse whenOpen / replyNote
SMSYou have a verified mobile + recent transaction~98% open, 15–25% replyHighest yield; keep it one line + link
EmailNo phone, or B2B with work addresses~20% open, 2–5% replyPersonalization merge tags lift response 20–30%
QR on receiptOn-site retail / hospitalitywalk-upPrint it; ask at the moment of satisfaction
In-app promptMobile app, after a success momentvariesTriggers the OS review sheet (App Store / Play)

Message anatomy (two sentences): name → one specific reference to what they bought → direct link to the review surface. No sentiment screen, no "if you're happy."

text
Hi Marta — thanks for the kitchen install last Tuesday. If you have 30 seconds,
your honest review helps other homeowners decide → [direct Google review link].

The link points straight to the review form (GBP "write a review" deep link, Trustpilot service-review invite, the app's store page). Never to an internal star-picker that branches on the rating — that's gating.

Respond — the playbook

Reply to every review within 48h (within 24h correlates with better local ranking; 52% of customers expect a reply within 7 days). On Google Play a developer response raises that review's rating by ~0.7 stars on average — replies are not optional hygiene, they move the number.

Review typeThe moveReply shapeSLA
5-star praiseThank + reinforce one specific they mentioned1–2 sentences, named, warm, on-voice48h
Positive + a question/askThank, then answer the question publiclyAnswer first, gratitude second48h
Vague 1–2 star (no detail)Acknowledge, invite the detail offline"Sorry to hear this — we'd like to understand, reach us at…"48h
Specific complaint (fair)Own it, move offline, state the fixThe sequence below24–48h
Suspected fake / off-topicFlag for removal and post a calm holding replySee "Flag vs reply"48h

The negative-review sequence (write it fresh every time; never paste a template):

  1. Acknowledge the person and the feeling, by name. No "we're sorry you feel that way."
  2. Own the specific thing that went wrong — name it, don't deflect.
  3. Move it offline — give a direct contact (name + email/phone), once.
  4. State the concrete fix or what you've changed, briefly.
  5. Invite an update — leave the door open for them to revise the review.
text
Bad  (defensive, public argument):
  "That's not what happened. Our records show you were 40 minutes late, which is
   why the install ran over. We followed our standard process."

Good (own → offline → fix → invite):
  "Hi James — you're right that the install ran past the window we promised, and
   that's on us. I'd like to make it right; please email me directly at
   ops@acme.co. We've since added a buffer to every booking so this doesn't
   repeat. — Lena, Ops Lead"
Show full SKILL.md (537 more words)Show less

Flag vs reply

Replying is the default. Flagging is the exception — and mass-flagging legitimate negatives is itself a reputation and policy risk. Flag for removal only when the review is:

  • Fake — from someone who never transacted.
  • Off-topic — not about your business / a different location.
  • Conflict of interest — competitor, ex-employee, personal feud.
  • Policy violation — profanity, hate, doxxing, illegal content.

A review that is negative, harsh, or even partly inaccurate but reflects a real experience is not flag-eligible. Answer it. Per-platform flag paths and dispute forms are in references/platform-apis.md.

The platforms (programmatic)

Most of this is offloaded to references/platform-apis.md (endpoints, scopes, roles, limits, gotchas). The three facts you must not get wrong, inline:

  • GBP reply is live and still on v4 — not migrated to v1, no announced deprecation:
    text
    PUT https://mybusiness.googleapis.com/v4/{name=accounts/*/locations/*/reviews/*}/reply
    scope: https://www.googleapis.com/auth/business.manage   # verified locations only
    This single PUT both creates and updates the reply.
  • The Google Q&A API is dead (shut down November 2025). Do not build against Questions-and-Answers endpoints — review listing + reply survive, Q&A does not.
  • Apple allows exactly one editable response per review via App Store Connect (get/create/update/delete; requires Account Holder, Admin, or Customer Support role). Apple also surfaces AI review summaries on iOS 18.4+, so themes in your reviews now feed an auto-generated digest — fix recurring complaints, don't just reply to them.

Reputation scorecard

Track six metrics per surface, reviewed weekly:

MetricWhat it isTarget signal
RatingAggregate starsTrend, not snapshot
VolumeTotal reviewsMore = more trust + rank weight
VelocityReviews/monthSteady inflow beats a stale 5.0
RecencyDays since last reviewFresh reviews are weighted heavier
Response rate %Replies ÷ reviewsAim ~100% — the +0.7-star Play effect compounds
Sentiment by themeComplaints/praise clusteredDrives fixes, feeds Apple's AI summary

Cluster the negatives by theme weekly. Three reviews about "slow checkout" is a product ticket, not three replies — route the fix, then close the loop in your replies.

Anti-patterns

Anti-patternWhy it failsDo instead
Gating (route unhappy away from the public link)Illegal FTC suppression, up to $53,088/violationAsk everyone the same neutral way
Buying / incentivizing-by-sentimentBanned; deceptive; finesDisclose any incentive, never tie it to positivity
Copy-paste reply on every reviewReads robotic; kills the +0.7-star effectWrite fresh, name one specific each time
Arguing in public / "that's not what happened"Every prospect reads you losingOwn it, move offline, state the fix
Ignoring positive reviewsLeaves trust + ranking weight on the tableReply to 5-stars too, within SLA
Replying off the brand-voice guideInconsistent, off-brand surfacePull traits from ../brand-voice/SKILL.md
Building on the Google Q&A APIShut down Nov 2025 — it's goneUse v4 reviews + updateReply only
Mass-flagging legitimate negativesPolicy risk; doesn't remove real feedbackFlag only fake/off-topic/conflict/policy

Verify the copy

Before you ship any request template or reply, run the copy-banlist linter — it fails on gating, sentiment-incentive, and dead-Q&A-API phrasing:

bash
./scripts/verify.sh path/to/review-copy.md

It's read-only and exits 0 on clean or empty input. See evals/README.md for how the capability eval is graded.

Cross-references

  • ../customer-support/SKILL.md — the private 1:1 ticket against an SLA
  • ../retention/SKILL.md — churn, NPS, save plays a bad review may signal
  • ../seo-geo/SKILL.md — making the profile rank beyond review signals
  • ../brand-voice/SKILL.md — the voice your replies are written in
  • ../social-publisher/SKILL.md — repurposing a glowing review into a post
  • references/platform-apis.md — per-surface endpoints, scopes, roles, limits, gotchas

© ericrisco, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in skills/review-management of ericrisco/rsc-harness.

  • SKILL.md
  • evals/README.md
  • evals/cases.yaml
  • references/platform-apis.md
  • scripts/verify.sh

Open the folder on GitHubat commit e3d5b33

Compare with similar skills

Review Management next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Review Management compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Review Management this skillericrisco/rsc-harness174—~2.9kAutomated safety check: PassMIT
Echo Feedbackjeremylongshore/tons-of-skills-marketplace2.8k—~1.2kAutomated safety check: NotesMIT
Review Managementappeeky/aso-skills2.2k—~1.5kAutomated safety check: PassMIT
Customer Supportaiskillstore/marketplace4307 repos~2.2kAutomated safety check: PassNone
Afa Cxafadtc/afa-dtc-skills168—~2.4kAutomated safety check: PassCustom licence
User Feedback Aggregationrampstackco/claude-skills941—~5.2kAutomated safety check: PassMIT

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Categories

Questions about Review Management

What does Review Management do?

A skill your agent uses when a public review needs an on-voice reply, when you need to earn more reviews legally, or when an aggregate rating is slipping across Google Business Profile, Trustpilot…. Review Management is an agent skill from ericrisco/rsc-harness. Use when a public review needs an on-voice reply, when you need to earn more reviews legally, or when an aggregate rating is slipping across Google Business Profile, Trustpilot, the App Store or Google Play — including deciding reply versus flag, getting an unfair one-star removed rather than merely answered, and wiring programmatic replies.

When should I use Review Management?

Review Management fits situations like: A public review needs an on-voice reply; you need to earn more reviews legally; an aggregate rating is slipping across Google Business Profile; google Play — including deciding reply versus flag.

How do I install Review Management in Claude Code?

Run `npx skills add ericrisco/rsc-harness --skill review-management -a claude-code`. Or copy the skill folder (skills/review-management in ericrisco/rsc-harness) into .claude/skills/review-management in your project. Claude Code loads it when a task matches its description.

How do I install Review Management in Codex?

Run `npx skills add ericrisco/rsc-harness --skill review-management -a codex`. Or copy the skill folder (skills/review-management in ericrisco/rsc-harness) into .agents/skills/review-management in your project. Codex loads it when a task matches its description.

Can I use Review Management in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ericrisco/rsc-harness --skill review-management -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review-management, .gemini/skills/review-management, .github/skills/review-management and .opencode/skills/review-management in your project.

What does Review Management need to run?

Going by SKILL.md and its folder, Review Management needs a shell for the scripts in its folder. Our summary lists: A Bash shell.

Does Review Management access the network?

SKILL.md names 1 domain. In commands or code: googleapis.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Review Management safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Review Management use?

Review Management is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Review Management use?

About 2.9k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1k tokens, read only when the agent opens those files.

What are the alternatives to Review Management?

Skills that share tags, products or a category with Review Management: Echo Feedback (jeremylongshore/tons-of-skills-marketplace, 2.8k stars), Review Management (appeeky/aso-skills, 2.2k stars), Customer Support (aiskillstore/marketplace, 430 stars) and Afa Cx (afadtc/afa-dtc-skills, 168 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Review Management?

ericrisco (a GitHub user) maintains it in ericrisco/rsc-harness, which has 174 GitHub stars. The repository holds 233 skills in this directory. The repository was last updated on October 7, 2026.

Source: ericrisco/rsc-harness on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.