Files
antigravity-skills-reference/skills/apify-audience-analysis/SKILL.md
Ahmed Rehan 2f55f046b9 feat: add 12 official Apify agent-skills for web scraping & data extraction (#165)
* feat: add 12 official Apify skills for web scraping and data extraction

Add the complete Apify agent-skills collection as official vendor skills,
bringing the total skill count from 954 to 966.

New skills:
- apify-actor-development: Develop, debug, and deploy Apify Actors
- apify-actorization: Convert existing projects into Apify Actors
- apify-audience-analysis: Audience demographics across social platforms
- apify-brand-reputation-monitoring: Track reviews, ratings, and sentiment
- apify-competitor-intelligence: Analyze competitor strategies and pricing
- apify-content-analytics: Track engagement metrics and campaign ROI
- apify-ecommerce: E-commerce data scraping for pricing intelligence
- apify-influencer-discovery: Find and evaluate influencers
- apify-lead-generation: B2B/B2C lead generation from multiple platforms
- apify-market-research: Market conditions and geographic opportunities
- apify-trend-analysis: Discover emerging trends across platforms
- apify-ultimate-scraper: Universal AI-powered web scraper

Existing skill fixes:
- design-orchestration: Add missing description, fix markdown list spacing
- multi-agent-brainstorming: Add missing description, fix markdown list spacing

Registry and documentation updates:
- Update skill count to 966+ across README.md, README.vi.md
- Add Apify to official sources in SOURCES.md and all README variants
- Register new skills in catalog.json, skills_index.json, bundles.json, aliases.json
- Update CATALOG.md category counts (data-ai: 152, infrastructure: 95)

Validation script improvements:
- Raise description length limit from 200 to 1024 characters
- Add empty description validation check
- Apply PEP 8 formatting (line length, spacing, trailing whitespace)

* refactor: truncate skill descriptions in SKILL.md files and revert  description length validation to 200 characters.

* feat: Add `apify-ultimate-scraper` to data-ai and move `apify-lead-generation` from business to general categories.
2026-03-01 10:02:50 +01:00

4.5 KiB

name, description
name description
apify-audience-analysis Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.

Audience Analysis

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