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apify-content-analytics

Collect engagement metrics for Instagram, Facebook, YouTube, and TikTok using Apify Actors, tools that extract platform data. Compare content performance, summarize key findings, and return selected results in chat or export full data as CSV or JSON.

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原文查看原文说明

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

查看安装方法

适用场景

  • Comparing engagement across social media posts
  • Analyzing Reels, Shorts, and other video performance
  • Tracking follower growth and branded hashtags
  • Exporting content metrics as CSV or JSON

包含的文件(2)

  • SKILL.md4.8 KB
  • reference/scripts/run_actor.js11.3 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Content Analytics

Track and analyze content performance using Apify Actors to extract engagement metrics from multiple platforms.

When to Use

  • You need engagement, growth, or ROI metrics for posts, reels, videos, ads, or hashtags.
  • The task is to use Apify Actors to collect cross-platform content performance data.
  • You need exported analytics results and a concise interpretation of what content is performing best.

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

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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