mcpbeat

Apify Brand Reputation Monitoring

lingxling/apify-brand-reputation-monitoring

Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.

4k tokens
context cost
the whole folder, loaded on every use
2
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
223
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/lingxling/awesome-skills-cn --skill apify-brand-reputation-monitoring

The instruction itself

11 sections, as written by the author

Brand Reputation Monitoring

Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.

When to Use

  • You need to monitor reviews, ratings, or brand mentions across social, travel, or map platforms.
  • The task is to select and run an Apify Actor for brand sentiment or reputation tracking.
  • You need exported monitoring results and a summary of reputation signals.

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

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

How to use it

Copy the folder

Take lingxling/apify-brand-reputation-monitoring from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference npm. Without those the skill loads but fails at the first command.