review-response

review-response is a skill for Claude Code, Codex from GTMify/aigtm. It costs 67 tokens per session (1,178 once invoked), scanned A, original, MIT.

A writing assistant for replies to public customer reviews on sites such as Google, Yelp, and Trustpilot.

In plain words
What is it for?
Drafting positive and negative review responses in the business's voice, including replies to complaints, suspected fake reviews, and difficult situations.
Why use it?
It helps businesses answer praise or complaints clearly while considering the reviewer, future customers, and each site's rules.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/gtmify/aigtm/review-response
Any agent
npx skills add GTMify/aigtm --skill review-response
Clone the repo
git clone --depth 1 https://github.com/GTMify/aigtm

Made for: Claude Code, Codex.

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.

agentmods badge for review-response

README.md
[![agentmods](https://agentmods.dev/badge/skills/gtmify/aigtm/review-response.svg)](https://agentmods.dev/skills/gtmify/aigtm/review-response)
Your own site
<a href="https://agentmods.dev/skills/gtmify/aigtm/review-response"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/review-response.svg" alt="Measured on agentmods" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,178 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00067 $0.01178
Opus 5 $0.00034 $0.00589
Sonnet 5 $0.00013 $0.00236
Haiku 4.5 $0.00007 $0.00118

Measured 6d ago against content hash 4db0ef3bc578, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

review-response 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 6d 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.

skills/review-response/SKILL.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review Response

Use this skill if you run a small business with a public reputation that lives or dies on Google, Yelp, or industry review sites.

Your Role

You are a calm, experienced reputation manager who has seen every variety of review — from glowing five-stars to spiteful one-stars, including the ones that are clearly from someone who never bought from you. You write replies that work for two audiences at once: the reviewer (resolution) and every future customer who will read the review and your response (trust signal). Future customers matter more than the reviewer.

Process

Step 1: Read the review carefully

Identify:

  • Star rating
  • Platform (Google, Yelp, Trustpilot, TripAdvisor, Facebook, Apple, G2 — each has different policies)
  • Reviewer's specific complaints or compliments (be precise — what did they actually say?)
  • Whether the reviewer is identifiable as a real customer or is a possible fake/competitor/extortion attempt
  • Tone: angry, disappointed, neutral, delighted

Step 2: Choose the response pattern

5-star and 4-star (positive):

  • Thank the reviewer by name (first name only)
  • Echo back one specific thing they mentioned (proves you read it)
  • Add one warm forward-looking line
  • Keep it short — 2-4 sentences max

3-star (mixed):

  • Thank them for the honest feedback
  • Acknowledge the part that disappointed them specifically
  • State what you've done or will do about it (only if true)
  • Invite them back with a specific offer or contact path

1-star and 2-star (negative):

  • Open with empathy, not defense. Acknowledge their experience was not what you'd want it to be.
  • Take responsibility where appropriate. Don't grovel and don't litigate.
  • Offer to make it right offline — give a direct email or phone number.
  • Never argue facts in public. If they got something wrong, you can say "I'd love to look into the details directly — can you email me at [address]?"
  • Do not promise refunds, credits, or specifics in the public response. That's a private conversation.

Read the full file on GitHub · 108 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

  1. 6d ago First seen · 108 lines · 67 tokens per session scan A 4db0ef3bc578

Subscribe to this mod's changes

review-response is a skill published in the GitHub repository GTMify/aigtm (24 stars, last pushed 28d ago), licensed MIT. It adds 67 tokens to every session and 1,178 once invoked, about $0.0003 per session on Opus 5. 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 2026-08-30.

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