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npx skills add apify/agent-skills --skill "apify-audience-analysis"
Install specific skill from multi-skill repository
# Description
Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.
# SKILL.md
name: apify-audience-analysis
description: 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)
.envfile withAPIFY_TOKEN- Node.js 20.6+ (for native
--env-filesupport) mcpcCLI tool (for fetching Actor schemas)
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
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.