npx skills add https://github.com/apify/awesome-skills
sickn33/agentic-awesome-skills
apify-audience-analysis
Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.
Installation
npx skills add sickn33/agentic-awesome-skills --skill apify-audience-analysis
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More details
Agent compatibility
Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.
Also listed on
Alternate registries and mirrors of this skill.
npx skills add https://github.com/apify/agent-skills
Repository health
main
Package contents
Files included with this skill beyond the listing page.
-
skill md
SKILL.md5,318 B -
docs
SUMMARY.md168 B
History
- First seen on skills.sh
- First recorded snapshot · 134 installs
SKILL.md
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)
.envfile withAPIFY_TOKEN- Node.js 20.6+ (for native
--env-filesupport) mcpcCLI 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:
- 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
- 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
APIFYTOKEN not found - Ask user to create .env with APIFYTOKEN=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.