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apify-brand-reputation-monitoring

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

Install / Use

npx skills add sickn33/agentic-awesome-skills --skill apify-brand-reputation-monitoring

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

92/100

Category

Operations

Supported Platforms

Universal

Our assessment of apify-brand-reputation-monitoring

apify-brand-reputation-monitoring scores 92/100 on our quality scale, 59th of 259 Operations skills we index (top 23%).

Its SKILL.md is 4.9 KB long, well organised into 11 sections with 5 code examples: a solid amount of guidance for an agent.

With 46,875 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
20/20
Description
12/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated yesterday, so apify-brand-reputation-monitoring is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-26. Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

apify-brand-reputation-monitoring compared with similar skills

All 4 of these similar skills score higher than apify-brand-reputation-monitoring; compare them before choosing.

SkillScoreStarsUpdatedFormat
apify-brand-reputation-monitoring (this skill)by sickn339246.9k1d agoSKILL.md
Agent-Reachby Panniantong10085.5k10d agoCLAUDE.md
headroomby headroomlabs-ai10073.8ktodayCLAUDE.md
Scraplingby D4Vinci10083.7ktodayMCP Server
LocalAIby mudler10049.3ktodayMCP Server

Frequently asked questions

How do I install apify-brand-reputation-monitoring?
Run npx skills add sickn33/agentic-awesome-skills --skill apify-brand-reputation-monitoring. The install tabs above show the steps for each supported agent.
Which AI agents does apify-brand-reputation-monitoring work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is apify-brand-reputation-monitoring safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is apify-brand-reputation-monitoring still maintained?
The repository was last updated yesterday, so apify-brand-reputation-monitoring is actively maintained.

name: apify-brand-reputation-monitoring description: "Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors." risk: critical source: community date_added: "2026-09-04"

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:

  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

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.

Related Skills

View on GitHub
GitHub Stars46.9k
CategoryOperations
Updated1d ago
Forks6.8k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions