Apify Content Analysis

--- 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 --- # 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 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: `bash 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):** `bash node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \ --actor "ACTOR_ID" \ --input 'JSON_INPUT' ` **CSV:** `bash 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:** `bash 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 APIFYTOKEN=yourtoken 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.