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apify-content-analytics

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

Install / Use

npx skills add sickn33/agentic-awesome-skills --skill apify-content-analytics

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

91/100

Supported Platforms

Universal

Our assessment of apify-content-analytics

apify-content-analytics scores 91/100 on our quality scale, 58th of 279 Data & Analytics skills we index (top 21%).

Its SKILL.md is 4.8 KB long, well organised into 11 sections with 5 code examples: a solid amount of guidance for an agent.

With 46,875 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
20/20
Description
15/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 3 days ago, so apify-content-analytics is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

apify-content-analytics compared with similar skills

All 4 of these similar skills score higher than apify-content-analytics; compare them before choosing.

SkillScoreStarsUpdatedFormat
apify-content-analytics (this skill)by sickn339146.9k3d agoSKILL.md
Agent-Reachby Panniantong10085.7k12d agoCLAUDE.md
headroomby headroomlabs-ai10073.9ktodayCLAUDE.md
crawl4aiby unclecode10084.4k2d agoMCP Server
Scraplingby D4Vinci10084.0ktodayMCP Server

Frequently asked questions

How do I install apify-content-analytics?
Run npx skills add sickn33/agentic-awesome-skills --skill apify-content-analytics. The install tabs above show the steps for each supported agent.
Which AI agents does apify-content-analytics work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is apify-content-analytics safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is apify-content-analytics still maintained?
The repository was last updated 3 days ago, so apify-content-analytics is actively maintained.

name: apify-content-analytics description: Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok. risk: critical source: community date_added: "2026-09-04"

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:

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.

Related Skills

View on GitHub
GitHub Stars46.9k
CategoryData
Updated3d ago
Forks6.8k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions