Skills Guide

Apify Content Analytics

VerifiedCaution

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

Sby Skills Guide Bot
ContentIntermediate
2508/13/2026
Claude Code
#apify#content-analytics#social-media#engagement#marketing

Recommended for

Claude CodeUI/UX designerSEO & contentProduct managerWriter / marketerSolo / indie hacker

Our review

This skill extracts and analyzes content engagement metrics from social platforms (Instagram, Facebook, YouTube, TikTok) using Apify Actors and a CLI tool.

Strengths

  • Covers multiple major social platforms in one workflow.
  • Provides a structured 5-step process from Actor selection to reporting.
  • Offers flexible output formats: quick answer, CSV, JSON.
  • Uses Apify's dynamic Actor schema for accurate input parameters.

Limitations

  • Requires an Apify account and token, plus Node.js and the mcpc tool.
  • Relies on external Apify Actors which may have usage costs or rate limits.
  • The actual output quality depends on the Actor's data completeness.
  • The Actor selection table may become outdated.
When to use it

When you need to assess social media content performance across platforms and produce structured engagement reports.

When not to use it

When you need real-time native analytics inside the platform, or when dealing with a platform not covered by the Apify Actors list.

Security analysis

Caution
Quality score85/100

The skill instructs running bash commands to manage an API token and execute Node.js scripts that interact with Apify's cloud API. While the purpose is legitimate analytics collection and no destructive or exfiltrating actions are evident, the use of shell, environment variable handling, and network calls warrants caution.

Findings
  • •Uses shell commands to extract and export APIFY_TOKEN from .env, which could expose the token in shell history or process listings
  • •Executes Node.js scripts with network access to Apify API, requiring trust in the bundled script (run_actor.js)

Examples

Instagram Post Analytics
Use the apify content analytics skill to get engagement metrics for my Instagram posts. Output the results as a CSV file.
YouTube Channel Growth
Run a YouTube analytics check for my channel using Apify, and show me the follower growth and top videos in a quick summary.
TikTok Hashtag Performance
Analyze TikTok content for the hashtag #viral and provide a JSON export of performance metrics.

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:

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

🔗 Связи

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