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Antigravity Apify Content Analytics

BSecurity

Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.

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  • Added September 19, 2026
content-marketinggobashreactnodeapiperformance

Works with

  • cli
  • api
  • mcp

Security analysis

B80/100
  • criticalSends environment variables or credentials to an external URL
  • mediumInstalls packages at runtime which could introduce malicious dependencies

Pro scans all 2 files and shows the line behind each finding

Scanned September 19, 2026

npx -y skills add ibragimov-oasis/oasis-languages-jp --skill antigravity-apify-content-analytics --agent claude-code

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SKILL.md
---
name: apify-content-analytics
description: Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
risk: unknown
source: community
tags:
  - domain/skills
  - artifact/skill
  - source/skills-antigravity
---

# Content Analytics

Track and analyze content performance using Apify Actors to extract engagement metrics from multiple platforms.

## 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: Identify content analytics type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analytics script
- [ ] Step 5: Summarize findings
```

### Step 1: Identify Content Analytics Type

Select the appropriate Actor based on analytics needs:

| User Need | Actor ID | Best For |
|-----------|----------|----------|
| Post engagement metrics | `apify/instagram-post-scraper` | Post performance |
| Reel performance | `apify/instagram-reel-scraper` | Reel analytics |
| Follower growth tracking | `apify/instagram-followers-count-scraper` | Growth metrics |
| Comment engagement | `apify/instagram-comment-scraper` | Comment analysis |
| Hashtag performance | `apify/instagram-hashtag-scraper` | Branded hashtags |
| Mention tracking | `apify/instagram-tagged-scraper` | Tag tracking |
| Comprehensive metrics | `apify/instagram-scraper` | Full data |
| API-based analytics | `apify/instagram-api-scraper` | API access |
| Facebook post performance | `apify/facebook-posts-scraper` | Post metrics |
| Reaction analysis | `apify/facebook-likes-scraper` | Engagement types |
| Facebook Reels metrics | `apify/facebook-reels-scraper` | Reels performance |
| Ad performance tracking | `apify/facebook-ads-scraper` | Ad analytics |
| Facebook comment analysis | `apify/facebook-comments-scraper` | Comment engagement |
| Page performance audit | `apify/facebook-pages-scraper` | Page metrics |
| YouTube video metrics | `streamers/youtube-scraper` | Video performance |
| YouTube Shorts analytics | `streamers/youtube-shorts-scraper` | Shorts performance |
| TikTok content metrics | `clockworks/tiktok-scraper` | TikTok analytics |

### 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., `apify/instagram-post-scraper`).

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 Findings

After completion, report:
- Number of content pieces analyzed
- File location and name
- Key performance insights
- Suggested next steps (deeper analysis, content optimization)

## 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`

## 🔗 Связи

- [[MOC - Skills]] — Skills library
- [[skills/skills-antigravity]] — Category: skills-antigravity

Files in this skill

  • SKILL.md4.4 KB
  • reference/scripts/run_actor.js11.5 KB

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