| name | review-reply |
| description | 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. |
| version | 1.0.2 |
| category | app-management |
| tags | ["app-store","ios","reviews","replies","monitoring","app-store-connect","ratings","customer-support","automation","indie-dev","solo-founder"] |
ReviewReply Skill
Automated App Store review monitor, reply drafter, and pattern detector. Monitors App Store Connect for new reviews, drafts warm on-brand replies for 1–3★ reviews using Claude, surfaces repeat-complaint patterns as bug alerts, and delivers a daily Telegram approval queue at 8am.
Skill Directory
skills/review-reply/
├── SKILL.md # This file — AI instructions & skill spec
├── README.md # Full usage docs and setup guide
├── scripts/
│ ├── monitor.py # Polls App Store Connect API for new reviews
│ ├── draft_reply.py # Drafts warm on-brand replies via Claude
│ ├── pattern_detector.py # Surfaces repeat-complaint patterns as bug alerts
│ └── queue_manager.py # Manages approval queue, Telegram 8am digest
├── references/
│ ├── app-store-connect-api.md # API auth setup (JWT, keys, endpoints)
│ └── reply-guidelines.md # Brand voice, tone, dos/don'ts
├── templates/
│ └── reply-prompts.md # Claude prompt templates per star rating
└── data/
├── reviews.json # Raw review store (auto-created)
├── queue.json # Pending approval queue (auto-created)
└── metrics.json # Response rate, timing, rating trends (auto-created)
1. Monitor Workflow
Script: scripts/monitor.py
What It Does
- Reads app list from config
- For each app, calls App Store Connect API →
/v1/apps/{id}/customerReviews
- Stores new reviews in
data/reviews.json (skips already-seen IDs)
- For reviews rated 1–3★: triggers
draft_reply.py automatically
- Passes all new reviews to
pattern_detector.py
- Logs run timestamp to
data/metrics.json
Run Schedule
- Designed to run via cron/launchd every 4 hours
- Manual run:
python3 scripts/monitor.py
Review Data Schema
{
"id": "string",
"app_id": "string",
"app_name": "string",
"rating": 1,
"title": "string",
"body": "string",
"reviewer": "string",
"territory": "string",
"created_date": "ISO8601",
"fetched_at": "ISO8601",
"reply_status": "pending|drafting|approved|posted|rejected|skipped",
"draft_reply": "string|null",
"approved_reply": "string|null",
"replied_at": "ISO8601|null"
}
3. Draft Reply Workflow
Script: scripts/draft_reply.py
What It Does
- Receives a review object (rating, title, body, app name)
- Selects the appropriate prompt template from
templates/reply-prompts.md based on star rating
- Calls Claude API with brand guidelines injected
- Stores draft in
data/queue.json with status pending
- Does NOT auto-post — all replies require human approval
Only Drafts For
- 1★, 2★, 3★ reviews (negative/neutral)
- 4★ and 5★ reviews: logged but no draft created (status =
skipped)
Output
{
"review_id": "string",
"app_name": "string",
"rating": 2,
"review_title": "string",
"review_body": "string",
"draft_reply": "string",
"drafted_at": "ISO8601",
"status": "pending",
"approved_reply": null,
"posted_at": null
}
4. Pattern Detection Workflow
Script: scripts/pattern_detector.py
What It Does
- Reads all reviews from the last 7 days in
data/reviews.json
- Groups by app
- Extracts complaint keywords/themes using Claude (semantic clustering)
- Threshold: If the same theme/complaint appears 3+ times in 7 days → bug alert
- Sends immediate Telegram alert (does not wait for 8am queue)
Alert Format (Telegram)
🚨 *Pattern Alert — FeedFare*
Complaint: "Feed not refreshing / stuck on loading"
Count: 5 reviews in the last 7 days
Rating avg: 1.8★
Recent examples:
• "App is broken, feed never loads" — 1★ (2026-02-18)
• "Stuck on spinning wheel for days" — 2★ (2026-02-17)
• "Used to work great, now broken" — 2★ (2026-02-16)
👉 Likely bug. Recommend investigating feed refresh logic.
Pattern Deduplication
- Patterns already alerted in the last 24h are not re-sent
- Each unique theme per app gets one alert per 24h window
- State stored in
data/metrics.json under pattern_alerts
5. Approval Queue Workflow
Script: scripts/queue_manager.py
Daily Digest (8am Telegram)
Every morning at 8:00 AM local time, queue_manager.py sends a Telegram message summarizing all pending replies:
📱 *ReviewReply Morning Queue — 3 Pending*
━━━━━━━━━━━━━━━━━━━
1️⃣ *FeedFare* — 2★ by @user123 (Feb 18)
"App crashes every time I open it"
📝 *Draft Reply:*
"Hi there! We're so sorry to hear about the crashes — that's definitely not the experience we want for you. Our team just pushed a fix in v2.1.1 that addresses the crash on launch. Please update and let us know if it helps! 🙏"
✅ /approve_1 ✏️ /edit_1 ❌ /reject_1
━━━━━━━━━━━━━━━━━━━
2️⃣ *FeedFare* — 1★ by @disappointed_dev (Feb 18)
...
━━━━━━━━━━━━━━━━━━━
📊 Stats: 12 reviewed · 8 replied · 67% response rate
Reply Approval Commands
/approve_N — marks reply as approved, posts to App Store Connect/edit_N <new text> — replaces draft with edited text, marks approved/reject_N — marks as rejected (no reply sent), removes from queue/skip_N — marks as skipped (no reply ever), removes from queue
Queue State Machine
new review
│
▼
[drafting] → draft failed → [error]
│
▼
[pending] ←→ [edited]
│
├─ approve → [approved] → post API → [posted]
├─ reject → [rejected]
└─ skip → [skipped]
Auto-Posting
When a reply is approved:
queue_manager.py calls App Store Connect API → POST /v1/customerReviewResponses- Marks status as
posted in data/queue.json
- Records
replied_at timestamp for metrics
6. Metrics Tracking
Data file: data/metrics.json
Tracked Metrics
| Metric | Description |
|---|
total_reviews | All-time review count per app |
reviews_this_week | Rolling 7-day count |
avg_rating | Current average star rating per app |
rating_trend | Direction vs previous 7-day period |
response_rate | % of 1-3★ reviews with approved/posted replies |
avg_response_time_hrs | Average hours between review and reply posted |
pending_count | Currently in queue |
posted_count | Successfully replied |
rejected_count | Intentionally skipped |
pattern_alerts | History of pattern alerts sent |
On-Demand Metrics Report
Say "review metrics" or "how are my apps doing?" and the AI will read data/metrics.json and format a summary.
7. AI Instructions — Conversational Commands
The AI handles these conversational patterns:
| User Says | AI Action |
|---|
| "check for new reviews" | Run python3 scripts/monitor.py |
| "show pending replies" | Read data/queue.json, list pending items |
| "approve reply 3" | Run python3 scripts/queue_manager.py --approve 3 |
| "edit reply 2: " | Run python3 scripts/queue_manager.py --edit 2 then pass text via stdin or temp file — never interpolate user text directly into shell strings |
| "reject reply 1" | Run python3 scripts/queue_manager.py --reject 1 |
| "draft a reply for review X" | Run python3 scripts/draft_reply.py --review-id X |
| "how are my apps doing?" | Read data/metrics.json, format summary |
| "show me recent reviews" | Read data/reviews.json, show last 10 |
| "any patterns this week?" | Run python3 scripts/pattern_detector.py --report |
| "response rate?" | Read metrics, show response_rate per app |
| "add app MyApp 1234567890" | Add to APPS config in monitor.py |
8. Environment Variables Required
| Variable | Description |
|---|
APP_STORE_KEY_ID | App Store Connect API Key ID |
APP_STORE_ISSUER_ID | App Store Connect Issuer ID |
APP_STORE_PRIVATE_KEY_PATH | Path to .p8 private key file |
ANTHROPIC_API_KEY | Claude API key for reply drafting |
TELEGRAM_BOT_TOKEN | Telegram bot token for notifications |
TELEGRAM_CHAT_ID | Your Telegram chat ID |
Store these in ~/.openclaw/.env or export in shell profile.
9. Cron / LaunchAgent Schedule
# App Store review monitor — every 4 hours
0 */4 * * * cd /Users/nick/.openclaw/workspace && python3 skills/review-reply/scripts/monitor.py >> /tmp/review-reply.log 2>&1
# Daily approval queue — 8am every day
0 8 * * * cd /Users/nick/.openclaw/workspace && python3 skills/review-reply/scripts/queue_manager.py --send-digest >> /tmp/review-reply.log 2>&1
See README.md for LaunchAgent plist setup.
10. Data Files Reference
All data lives in data/ and is plain JSON — easy to inspect, backup, and migrate.
| File | Purpose |
|---|
data/reviews.json | All fetched reviews, one object per review |
data/queue.json | Active reply queue (pending/approved/rejected items) |
data/metrics.json | Aggregated metrics, pattern alert history |
Backup
cp -r skills/review-reply/data/ ~/review-reply-backup/
