multiAI Summary Pending
apify-content-analytics
Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
28,273 stars
bysickn33
Installation
Claude Code / Cursor / Codex
$curl -o ~/.claude/skills/apify-content-analytics/SKILL.md --create-dirs "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/plugins/antigravity-awesome-skills-claude/skills/apify-content-analytics/SKILL.md"
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/apify-content-analytics/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How apify-content-analytics Compares
| Feature / Agent | apify-content-analytics | Standard Approach |
|---|---|---|
| Platform Support | multi | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
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
# 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`