apify-content-analytics

apify/agent-skills · updated Apr 8, 2026

$npx skills add https://github.com/apify/agent-skills --skill apify-content-analytics
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summary

Multi-platform content analytics via Apify Actors for Instagram, Facebook, YouTube, and TikTok.

  • Supports 17+ specialized Actors covering posts, reels, stories, comments, hashtags, followers, and ads across all four platforms
  • Dynamically fetches Actor schemas using mcpc CLI to determine required inputs and available output fields
  • Outputs results in three formats: quick chat display, CSV export, or JSON export with customizable result counts
  • Requires Apify token in .env file and Nod
skill.md

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

Discussion

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general reviews

Ratings

4.754 reviews
  • Advait Harris· Dec 28, 2024

    Keeps context tight: apify-content-analytics is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Valentina Patel· Dec 24, 2024

    We added apify-content-analytics from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Chaitanya Patil· Dec 16, 2024

    Useful defaults in apify-content-analytics — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Advait Sethi· Dec 12, 2024

    I recommend apify-content-analytics for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Nikhil Kim· Dec 8, 2024

    apify-content-analytics fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Min White· Nov 27, 2024

    apify-content-analytics is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Xiao Li· Nov 23, 2024

    apify-content-analytics reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Xiao Wang· Nov 19, 2024

    We added apify-content-analytics from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • James Shah· Nov 15, 2024

    Keeps context tight: apify-content-analytics is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Piyush G· Nov 7, 2024

    apify-content-analytics has been reliable in day-to-day use. Documentation quality is above average for community skills.

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