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apify-content-analytics

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

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SKILL.md

Full skill instructions

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 (for fetching Actor schemas)

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 NeedActor IDBest For
Post engagement metricsapify/​instagram-post-scraperPost performance
Reel performanceapify/​instagram-reel-scraperReel analytics
Follower growth trackingapify/​instagram-followers-count-scraperGrowth metrics
Comment engagementapify/​instagram-comment-scraperComment analysis
Hashtag performanceapify/​instagram-hashtag-scraperBranded hashtags
Mention trackingapify/​instagram-tagged-scraperTag tracking
Comprehensive metricsapify/​instagram-scraperFull data
API-based analyticsapify/​instagram-api-scraperAPI access
Facebook post performanceapify/​facebook-posts-scraperPost metrics
Reaction analysisapify/​facebook-likes-scraperEngagement types
Facebook Reels metricsapify/​facebook-reels-scraperReels performance
Ad performance trackingapify/​facebook-ads-scraperAd analytics
Facebook comment analysisapify/​facebook-comments-scraperComment engagement
Page performance auditapify/​facebook-pages-scraperPage metrics
YouTube video metricsstreamers/​youtube-scraperVideo performance
YouTube Shorts analyticsstreamers/​youtube-shorts-scraperShorts performance
TikTok content metricsclockworks/​tiktok-scraperTikTok analytics

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., 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):

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 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