Individual skill
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.
review-response-writer/SKILL.md
Source commit b2267d9171af4f56848d82992381b20b89b44056
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Instructions only
- Last checked
- Nov 10, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 422
- Repository last updated
- Oct 20, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude Repository topic
- claude-code Repository topic
- claude-skills Repository topic
- developer-tools Repository topic
- llm Repository topic
- prompt-engineering Repository topic
- sales-automation Repository topic
- legal Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 3,752 bytes
Read excerpt
# 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.