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apify-brand-reputation-monitoring

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

28,273 stars

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/apify-brand-reputation-monitoring/SKILL.md --create-dirs "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/plugins/antigravity-awesome-skills-claude/skills/apify-brand-reputation-monitoring/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/apify-brand-reputation-monitoring/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How apify-brand-reputation-monitoring Compares

Feature / Agentapify-brand-reputation-monitoringStandard Approach
Platform SupportmultiLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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

Which AI agents support this skill?

This skill is compatible with multi.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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:

```bash
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):**
```bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'
```

**CSV:**
```bash
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:**
```bash
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`