Agent-Skills.md

Agent Skills: Review Response Writer

Respond to Google, Yelp, and industry reviews in the owner's voice -- gracious on the 5-stars, masterful on the 1-stars. Handles the angry customer, the unfair review, the fake review, and the one that mentions a legal or health issue. Every response written for the thousand future customers reading it.

UncategorizedID: OneWave-AI/claude-skills/review-response-writer

Repository

OneWave-AI/claude-skills
OneWave-AILicense: MIT
22238

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pnpm dlx add-skill https://github.com/OneWave-AI/claude-skills/tree/HEAD/review-response-writer

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review-response-writer/SKILL.md

Skill Metadata

Name
review-response-writer
Description
Respond to Google, Yelp, and industry reviews in the owner's voice -- gracious on the 5-stars, masterful on the 1-stars. Handles the angry customer, the unfair review, the fake review, and the one that mentions a legal or health issue. Every response written for the thousand future customers reading it.

Review Response Writer

The response to a bad review is not for the reviewer -- it is for every prospect who reads it for the next five years. Input: the review text (pasted, exported, or fetched from the profile), and on first run a few existing responses or a note on how the owner talks. Output: responses ready to post, plus escalation flags for the ones that need more than words.

Workflow

  1. Learn the voice. From past responses or the owner's description: warmth level, formality, sign-off style, whether they use names. Small-business responses that sound like the actual owner outperform corporate-polished ones -- keep contractions, keep personality.
  2. Triage each review:
    • GLOW (4-5 stars) -- thank specifically (echo the detail they praised, never generic), reinforce the service mentioned (it is searchable text), invite them back.
    • LEGITIMATE COMPLAINT -- acknowledge the specific failure without excuses, state the fix made, take it offline with a real contact, never argue. No coupons in public (it trains complaint-for-discount).
    • UNFAIR/MISTAKEN -- correct the record factually and briefly ("Our records show we honored the quoted price of...") while staying gracious; readers can tell who is being reasonable.
    • SUSPECTED FAKE (no record of the customer, competitor patterns) -- respond once, neutrally ("We have no record of serving you -- contact us and we'll make it right"), and output the platform's removal-request steps with the policy grounds.
    • ESCALATE -- anything mentioning injury, illness, discrimination, legal threats, or an employee by name in an accusation: draft nothing final; flag for the owner and, where serious, counsel, with a holding-pattern response option.
  3. Draft. Responses under 100 words for positives, under 150 for negatives. Vary structure across a batch -- ten identical-template responses read as a bot and undo the effort.
  4. Batch report. For a backlog: respond oldest-negative first (unanswered negatives do compounding damage), then recent positives. Note patterns worth fixing upstream -- three reviews mentioning wait times is an operations finding, not a writing task.

Rules

  • Never admit legal fault, discuss health/medical specifics, or confirm someone was a customer on platforms where that itself is sensitive (medical, legal, financial services -- respond without confirming the relationship).
  • Never argue, never sarcasm, never match the reviewer's temperature. The audience is the reader, not the reviewer.
  • Specificity is the tell of sincerity: echo one concrete detail from every review; a response that could sit under any review helps nobody.
  • Public forgiveness, private resolution: the public reply shows character, the offline contact fixes the problem.
  • Fake-review accusations stay out of the public response -- neutrality publicly, evidence in the removal request.
  • Response velocity matters: recommend responding to negatives within 24-48 hours and set that as the standing cadence.

Quick Commands

  • "Respond to this review" -- single review, voice-matched
  • "Clear my backlog [export/profile]" -- triaged batch with drafts
  • "Handle this 1-star" -- deep treatment: response + offline script + removal assessment if warranted
  • "What are my reviews telling me?" -- the upstream operations patterns