Agent Skills: Brand Reputation Monitoring

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.

UncategorizedID: apify/agent-skills/apify-brand-reputation-monitoring

Install this agent skill to your local

pnpm dlx add-skill https://github.com/apify/agent-skills/tree/HEAD/skills/apify-brand-reputation-monitoring

Skill Files

Browse the full folder contents for apify-brand-reputation-monitoring.

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skills/apify-brand-reputation-monitoring/SKILL.md

Skill Metadata

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)

  • .env file with APIFY_TOKEN
  • Node.js 20.6+ (for native --env-file support)
  • mcpc CLI tool: npm install -g @apify/mcpc

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