133 lines
4.8 KiB
Markdown
133 lines
4.8 KiB
Markdown
---
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name: apify-brand-reputation-monitoring
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description: "Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors."
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risk: unknown
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source: community
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---
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# Brand Reputation Monitoring
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Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.
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## When to Use
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- You need to monitor reviews, ratings, or brand mentions across social, travel, or map platforms.
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- The task is to select and run an Apify Actor for brand sentiment or reputation tracking.
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- You need exported monitoring results and a summary of reputation signals.
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## Prerequisites
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(No need to check it upfront)
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- `.env` file with `APIFY_TOKEN`
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- Node.js 20.6+ (for native `--env-file` support)
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- `mcpc` CLI tool: `npm install -g @apify/mcpc`
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## Workflow
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Copy this checklist and track progress:
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```
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Task Progress:
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- [ ] Step 1: Determine data source (select Actor)
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- [ ] Step 2: Fetch Actor schema via mcpc
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- [ ] Step 3: Ask user preferences (format, filename)
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- [ ] Step 4: Run the monitoring script
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- [ ] Step 5: Summarize results
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```
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### Step 1: Determine Data Source
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Select the appropriate Actor based on user needs:
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| User Need | Actor ID | Best For |
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|-----------|----------|----------|
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| Google Maps reviews | `compass/crawler-google-places` | Business reviews, ratings |
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| Google Maps review export | `compass/Google-Maps-Reviews-Scraper` | Dedicated review scraping |
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| Booking.com hotels | `voyager/booking-scraper` | Hotel data, scores |
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| Booking.com reviews | `voyager/booking-reviews-scraper` | Detailed hotel reviews |
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| TripAdvisor reviews | `maxcopell/tripadvisor-reviews` | Attraction/restaurant reviews |
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| Facebook reviews | `apify/facebook-reviews-scraper` | Page reviews |
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| Facebook comments | `apify/facebook-comments-scraper` | Post comment monitoring |
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| Facebook page metrics | `apify/facebook-pages-scraper` | Page ratings overview |
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| Facebook reactions | `apify/facebook-likes-scraper` | Reaction type analysis |
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| Instagram comments | `apify/instagram-comment-scraper` | Comment sentiment |
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| Instagram hashtags | `apify/instagram-hashtag-scraper` | Brand hashtag monitoring |
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| Instagram search | `apify/instagram-search-scraper` | Brand mention discovery |
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| Instagram tagged posts | `apify/instagram-tagged-scraper` | Brand tag tracking |
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| Instagram export | `apify/export-instagram-comments-posts` | Bulk comment export |
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| Instagram comprehensive | `apify/instagram-scraper` | Full Instagram monitoring |
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| Instagram API | `apify/instagram-api-scraper` | API-based monitoring |
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| YouTube comments | `streamers/youtube-comments-scraper` | Video comment sentiment |
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| TikTok comments | `clockworks/tiktok-comments-scraper` | TikTok sentiment |
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### Step 2: Fetch Actor Schema
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Fetch the Actor's input schema and details dynamically using mcpc:
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```bash
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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"
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```
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Replace `ACTOR_ID` with the selected Actor (e.g., `compass/crawler-google-places`).
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This returns:
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- Actor description and README
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- Required and optional input parameters
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- Output fields (if available)
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### Step 3: Ask User Preferences
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Before running, ask:
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1. **Output format**:
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- **Quick answer** - Display top few results in chat (no file saved)
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- **CSV** - Full export with all fields
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- **JSON** - Full export in JSON format
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2. **Number of results**: Based on character of use case
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### Step 4: Run the Script
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**Quick answer (display in chat, no file):**
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```bash
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node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
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--actor "ACTOR_ID" \
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--input 'JSON_INPUT'
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```
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**CSV:**
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```bash
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node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
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--actor "ACTOR_ID" \
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--input 'JSON_INPUT' \
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--output YYYY-MM-DD_OUTPUT_FILE.csv \
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--format csv
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```
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**JSON:**
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```bash
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node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
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--actor "ACTOR_ID" \
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--input 'JSON_INPUT' \
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--output YYYY-MM-DD_OUTPUT_FILE.json \
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--format json
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```
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### Step 5: Summarize Results
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After completion, report:
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- Number of reviews/mentions found
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- File location and name
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- Key fields available
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- Suggested next steps (sentiment analysis, filtering)
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## Error Handling
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`APIFY_TOKEN not found` - Ask user to create `.env` with `APIFY_TOKEN=your_token`
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`mcpc not found` - Ask user to install `npm install -g @apify/mcpc`
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`Actor not found` - Check Actor ID spelling
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`Run FAILED` - Ask user to check Apify console link in error output
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`Timeout` - Reduce input size or increase `--timeout`
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## Limitations
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- Use this skill only when the task clearly matches the scope described above.
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- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
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- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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