#app-store #app-store-connect #replies #reviews

App Store ReviewReply

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.

Nick@nicholasrae

Install

openclaw skills install @nicholasrae/nicholasrae-review-reply

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

text

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

json

{
  "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

json

{
  "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)

text

🚨 *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:

text

📱 *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

text

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

text

# 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

bash

cp -r skills/review-reply/data/ ~/review-reply-backup/

App Store ReviewReply

Install

ReviewReply Skill

Skill Directory

1. Monitor Workflow

What It Does

Run Schedule

Review Data Schema

3. Draft Reply Workflow

What It Does

Only Drafts For

Output

4. Pattern Detection Workflow

What It Does

Alert Format (Telegram)

Pattern Deduplication

5. Approval Queue Workflow

Daily Digest (8am Telegram)

Reply Approval Commands

Queue State Machine

Auto-Posting

6. Metrics Tracking

Tracked Metrics

On-Demand Metrics Report

7. AI Instructions — Conversational Commands

8. Environment Variables Required

9. Cron / LaunchAgent Schedule

10. Data Files Reference

Backup

Related skills