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apify-audience-analysis

Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.

Install / Use

npx skills add sickn33/agentic-awesome-skills --skill apify-audience-analysis

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-audience-analysis

apify-audience-analysis scores 91/100 on our quality scale, 427th of 2,860 Development & Engineering skills we index (top 15%).

Its SKILL.md is 5.2 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-audience-analysis 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-audience-analysis compared with similar skills

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

SkillScoreStarsUpdatedFormat
apify-audience-analysis (this skill)by sickn339146.9k3d agoSKILL.md
Agent-Reachby Panniantong10085.7k12d agoCLAUDE.md
headroomby headroomlabs-ai10073.9ktodayCLAUDE.md
ai-job-searchby MadsLorentzen10044.1ktodayCLAUDE.md
claude-howtoby luongnv8910041.7k1d agoCLAUDE.md

Frequently asked questions

How do I install apify-audience-analysis?
Run npx skills add sickn33/agentic-awesome-skills --skill apify-audience-analysis. The install tabs above show the steps for each supported agent.
Which AI agents does apify-audience-analysis 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-audience-analysis 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-audience-analysis still maintained?
The repository was last updated 3 days ago, so apify-audience-analysis is actively maintained.

name: apify-audience-analysis description: Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok. risk: critical source: community date_added: "2026-09-04"

Audience Analysis

Analyze and understand your audience using Apify Actors to extract follower demographics, engagement patterns, and behavior data from multiple platforms.

When to Use

  • You need audience demographics, engagement patterns, or follower behavior from social platforms.
  • The task is to choose and run Apify Actors for audience analysis across Facebook, Instagram, YouTube, or TikTok.
  • You need structured extraction plus a summarized interpretation of audience findings.

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 audience analysis type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analysis script
- [ ] Step 5: Summarize findings

Step 1: Identify Audience Analysis Type

Select the appropriate Actor based on analysis needs:

| User Need | Actor ID | Best For | |-----------|----------|----------| | Facebook follower demographics | apify/facebook-followers-following-scraper | FB followers/following lists | | Facebook engagement behavior | apify/facebook-likes-scraper | FB post likes analysis | | Facebook video audience | apify/facebook-reels-scraper | FB Reels viewers | | Facebook comment analysis | apify/facebook-comments-scraper | FB post/video comments | | Facebook content engagement | apify/facebook-posts-scraper | FB post engagement metrics | | Instagram audience sizing | apify/instagram-profile-scraper | IG profile demographics | | Instagram location-based | apify/instagram-search-scraper | IG geo-tagged audience | | Instagram tagged network | apify/instagram-tagged-scraper | IG tag network analysis | | Instagram comprehensive | apify/instagram-scraper | Full IG audience data | | Instagram API-based | apify/instagram-api-scraper | IG API access | | Instagram follower counts | apify/instagram-followers-count-scraper | IG follower tracking | | Instagram comment export | apify/export-instagram-comments-posts | IG comment bulk export | | Instagram comment analysis | apify/instagram-comment-scraper | IG comment sentiment | | YouTube viewer feedback | streamers/youtube-comments-scraper | YT comment analysis | | YouTube channel audience | streamers/youtube-channel-scraper | YT channel subscribers | | TikTok follower demographics | clockworks/tiktok-followers-scraper | TT follower lists | | TikTok profile analysis | clockworks/tiktok-profile-scraper | TT profile demographics | | TikTok comment analysis | clockworks/tiktok-comments-scraper | TT comment engagement |

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/facebook-followers-following-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 audience members/profiles analyzed
  • File location and name
  • Key demographic insights
  • Suggested next steps (deeper analysis, segmentation)

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
CategoryDevelopment
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