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apify-content-analytics

apify-content-analytics

github.com/apifyMarketing & growth2.5k2.5k installsUpdated 1w ago
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About apify-content-analytics

A skill for extracting engagement metrics with Apify Actors and analyzing content performance across platforms. It helps marketers choose an Actor for a specific analytics task, run it, and review or export the results.

Key features

  1. 01Select Apify Actors by analytics need
  2. 02Fetch Actor input schemas dynamically
  3. 03Run analysis and summarize findings
  4. 04Display results or export as CSV or JSON

Use cases

  1. 01Compare Instagram post or Reel performance
  2. 02Track Facebook post and ad metrics
  3. 03Analyze YouTube and TikTok content data

MCP support

Uses mcpc to connect to mcp.apify.com and retrieve details and input schemas for selected Actors, which the skill then runs.

Install

Copy the command and run it in a terminal.

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

After installing, type/apify-content-analyticsin Claude Code to confirm it loaded.

Bundled filesreference/scripts/run_actor.js

Details

From the project README

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 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

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