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apify-audience-analysis

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

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含まれるファイル(2)

  • SKILL.md5.2 KB
  • reference/scripts/run_actor.js11.5 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

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 NeedActor IDBest For
Facebook follower demographicsapify/facebook-followers-following-scraperFB followers/following lists
Facebook engagement behaviorapify/facebook-likes-scraperFB post likes analysis
Facebook video audienceapify/facebook-reels-scraperFB Reels viewers
Facebook comment analysisapify/facebook-comments-scraperFB post/video comments
Facebook content engagementapify/facebook-posts-scraperFB post engagement metrics
Instagram audience sizingapify/instagram-profile-scraperIG profile demographics
Instagram location-basedapify/instagram-search-scraperIG geo-tagged audience
Instagram tagged networkapify/instagram-tagged-scraperIG tag network analysis
Instagram comprehensiveapify/instagram-scraperFull IG audience data
Instagram API-basedapify/instagram-api-scraperIG API access
Instagram follower countsapify/instagram-followers-count-scraperIG follower tracking
Instagram comment exportapify/export-instagram-comments-postsIG comment bulk export
Instagram comment analysisapify/instagram-comment-scraperIG comment sentiment
YouTube viewer feedbackstreamers/youtube-comments-scraperYT comment analysis
YouTube channel audiencestreamers/youtube-channel-scraperYT channel subscribers
TikTok follower demographicsclockworks/tiktok-followers-scraperTT follower lists
TikTok profile analysisclockworks/tiktok-profile-scraperTT profile demographics
TikTok comment analysisclockworks/tiktok-comments-scraperTT 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 enprojectnment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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