Antigravity-awesome-skills apify-audience-analysis

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

install

source · Clone the upstream repo

git clone https://github.com/sickn33/antigravity-awesome-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/sickn33/antigravity-awesome-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/antigravity-awesome-skills-claude/skills/apify-audience-analysis" ~/.claude/skills/sickn33-antigravity-awesome-skills-apify-audience-analysis && rm -rf "$T"

manifest: plugins/antigravity-awesome-skills-claude/skills/apify-audience-analysis/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)

```
.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:

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

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.