apify-brand-reputation-monitoring

SKILL.md

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:

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

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