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npx skills add apify/agent-skills --skill "apify-brand-reputation-monitoring"
Install specific skill from multi-skill repository
# Description
Track reviews, ratings, sentiment, and brand mentions across Google Maps, Booking.com, TripAdvisor, Facebook, Instagram, YouTube, and TikTok. Use when user asks to monitor brand reputation, analyze reviews, track mentions, or gather customer feedback.
# SKILL.md
name: apify-brand-reputation-monitoring
description: Track reviews, ratings, sentiment, and brand mentions across Google Maps, Booking.com, TripAdvisor, Facebook, Instagram, YouTube, and TikTok. Use when user asks to monitor brand reputation, analyze reviews, track mentions, or gather customer feedback.
Brand Reputation Monitoring
Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
Prerequisites
(No need to check it upfront)
.envfile withAPIFY_TOKEN- Node.js 20.6+ (for native
--env-filesupport) mcpcCLI tool (for fetching Actor schemas)
Workflow
Copy this checklist and track progress:
Task Progress:
- [ ] Step 1: Determine data source (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the monitoring script
- [ ] Step 5: Summarize results
Step 1: Determine Data Source
Select the appropriate Actor based on user needs:
| User Need | Actor ID | Best For |
|---|---|---|
| Google Maps reviews | compass/crawler-google-places |
Business reviews, ratings |
| Google Maps review export | compass/Google-Maps-Reviews-Scraper |
Dedicated review scraping |
| Booking.com hotels | voyager/booking-scraper |
Hotel data, scores |
| Booking.com reviews | voyager/booking-reviews-scraper |
Detailed hotel reviews |
| TripAdvisor reviews | maxcopell/tripadvisor-reviews |
Attraction/restaurant reviews |
| Facebook reviews | apify/facebook-reviews-scraper |
Page reviews |
| Facebook comments | apify/facebook-comments-scraper |
Post comment monitoring |
| Facebook page metrics | apify/facebook-pages-scraper |
Page ratings overview |
| Facebook reactions | apify/facebook-likes-scraper |
Reaction type analysis |
| Instagram comments | apify/instagram-comment-scraper |
Comment sentiment |
| Instagram hashtags | apify/instagram-hashtag-scraper |
Brand hashtag monitoring |
| Instagram search | apify/instagram-search-scraper |
Brand mention discovery |
| Instagram tagged posts | apify/instagram-tagged-scraper |
Brand tag tracking |
| Instagram export | apify/export-instagram-comments-posts |
Bulk comment export |
| Instagram comprehensive | apify/instagram-scraper |
Full Instagram monitoring |
| Instagram API | apify/instagram-api-scraper |
API-based monitoring |
| YouTube comments | streamers/youtube-comments-scraper |
Video comment sentiment |
| TikTok comments | clockworks/tiktok-comments-scraper |
TikTok sentiment |
Step 2: Fetch Actor Schema
Fetch the Actor's input schema and details dynamically using mcpc:
export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"
Replace ACTOR_ID with the selected Actor (e.g., compass/crawler-google-places).
This returns:
- Actor description and README
- Required and optional input parameters
- Output fields (if available)
Step 3: Ask User Preferences
Before running, ask:
1. Output format:
- Quick answer - Display top few results in chat (no file saved)
- CSV - Full export with all fields
- JSON - Full export in JSON format
2. Number of results: Based on character of use case
Step 4: Run the Script
Quick answer (display in chat, no file):
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT'
CSV:
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT' \
--output YYYY-MM-DD_OUTPUT_FILE.csv \
--format csv
JSON:
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
--actor "ACTOR_ID" \
--input 'JSON_INPUT' \
--output YYYY-MM-DD_OUTPUT_FILE.json \
--format json
Step 5: Summarize Results
After completion, report:
- Number of reviews/mentions found
- File location and name
- Key fields available
- Suggested next steps (sentiment analysis, filtering)
Error Handling
APIFY_TOKEN not found - Ask user to create .env with APIFY_TOKEN=your_token
mcpc not found - Ask user to install npm install -g @apify/mcpc
Actor not found - Check Actor ID spelling
Run FAILED - Ask user to check Apify console link in error output
Timeout - Reduce input size or increase --timeout
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.