review-reply
Automatically monitors your App Store reviews and drafts warm, on-brand replies for 1–3 star reviews — so unhappy users hear back fast. Connects to App Store Connect API, detects repeat complaint patterns as bug signals, and delivers a daily approval queue to Telegram at 8am. You approve, it sends. Supports multiple apps simultaneously.
Why use this skill?
Automate your App Store review replies and bug tracking. This OpenClaw skill drafts warm responses and alerts you to common user complaints via Telegram daily.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/nicholasrae/nicholasrae-review-replyWhat This Skill Does
The Review-Reply skill is a specialized automation agent designed to help developers and product managers manage their App Store reputation without sacrificing personal touch. By integrating directly with the App Store Connect API, this skill acts as a vigilant monitor that scans for new user feedback, automatically filters for negative sentiment (1–3 star ratings), and leverages Claude to draft warm, brand-aligned responses. Instead of requiring you to manually check the dashboard, it aggregates pending replies into a daily Telegram queue delivered at 8:00 AM, ensuring you only spend a few minutes a day managing your store presence. Beyond simple replies, the skill includes a pattern detection engine that scans review text to identify recurring bug reports or technical friction points, surfacing these as actionable alerts before they result in a mass exodus of users.
Installation
To install this skill, ensure your OpenClaw environment is authenticated with your App Store Connect credentials. Run the following command in your terminal: clawhub install openclaw/skills/skills/nicholasrae/nicholasrae-review-reply. Once installed, configure your API keys by placing them in the references/app-store-connect-api.md path. The skill will automatically initialize the necessary JSON files in the /data directory upon its first run.
Use Cases
- Proactive Customer Support: Quickly address user frustrations for 1-3 star reviews to reduce churn and improve ratings.
- Automated Bug Tracking: Use the pattern detector to spot trends in negative reviews, such as users complaining about a specific crash after a recent update, allowing your engineering team to pivot faster.
- Efficiency for Indie Devs: Save hours of manual review management by moving from individual review auditing to a single daily summary digest.
Example Prompts
- "OpenClaw, show me the pending review queue for my Productivity App and tell me if the pattern detector found any new bugs in the latest batch."
- "OpenClaw, approve all pending replies for my Fitness App, but exclude the one from 'User123'—I want to draft that one myself."
- "OpenClaw, update the brand voice guidelines to be more concise and professional in the
reply-guidelines.mdfile for all future review drafts."
Tips & Limitations
For the best results, regularly update the reply-guidelines.md file to reflect your brand's evolving voice. Note that this skill is specifically optimized for negative and neutral feedback; 4 and 5-star reviews are tracked but purposely ignored for drafting to keep your queue focused on critical issues. Always double-check drafts before approving, as automated sentiment analysis is helpful but not a replacement for human oversight in sensitive situations.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-nicholasrae-nicholasrae-review-reply": {
"enabled": true,
"auto_update": true
}
}
}Tags
Flags: network-access, file-write, file-read, external-api
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