* 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.
122 lines
4.5 KiB
Markdown
122 lines
4.5 KiB
Markdown
---
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name: apify-audience-analysis
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description: Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.
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---
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# Audience Analysis
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Analyze and understand your audience using Apify Actors to extract follower demographics, engagement patterns, and behavior data from multiple platforms.
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## Prerequisites
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(No need to check it upfront)
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- `.env` file with `APIFY_TOKEN`
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- Node.js 20.6+ (for native `--env-file` support)
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- `mcpc` CLI tool: `npm install -g @apify/mcpc`
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## Workflow
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Copy this checklist and track progress:
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```
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Task Progress:
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- [ ] Step 1: Identify audience analysis type (select Actor)
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- [ ] Step 2: Fetch Actor schema via mcpc
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- [ ] Step 3: Ask user preferences (format, filename)
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- [ ] Step 4: Run the analysis script
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- [ ] Step 5: Summarize findings
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```
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### Step 1: Identify Audience Analysis Type
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Select the appropriate Actor based on analysis needs:
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| User Need | Actor ID | Best For |
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|-----------|----------|----------|
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| Facebook follower demographics | `apify/facebook-followers-following-scraper` | FB followers/following lists |
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| Facebook engagement behavior | `apify/facebook-likes-scraper` | FB post likes analysis |
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| Facebook video audience | `apify/facebook-reels-scraper` | FB Reels viewers |
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| Facebook comment analysis | `apify/facebook-comments-scraper` | FB post/video comments |
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| Facebook content engagement | `apify/facebook-posts-scraper` | FB post engagement metrics |
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| Instagram audience sizing | `apify/instagram-profile-scraper` | IG profile demographics |
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| Instagram location-based | `apify/instagram-search-scraper` | IG geo-tagged audience |
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| Instagram tagged network | `apify/instagram-tagged-scraper` | IG tag network analysis |
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| Instagram comprehensive | `apify/instagram-scraper` | Full IG audience data |
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| Instagram API-based | `apify/instagram-api-scraper` | IG API access |
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| Instagram follower counts | `apify/instagram-followers-count-scraper` | IG follower tracking |
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| Instagram comment export | `apify/export-instagram-comments-posts` | IG comment bulk export |
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| Instagram comment analysis | `apify/instagram-comment-scraper` | IG comment sentiment |
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| YouTube viewer feedback | `streamers/youtube-comments-scraper` | YT comment analysis |
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| YouTube channel audience | `streamers/youtube-channel-scraper` | YT channel subscribers |
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| TikTok follower demographics | `clockworks/tiktok-followers-scraper` | TT follower lists |
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| TikTok profile analysis | `clockworks/tiktok-profile-scraper` | TT profile demographics |
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| TikTok comment analysis | `clockworks/tiktok-comments-scraper` | TT comment engagement |
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### Step 2: Fetch Actor Schema
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Fetch the Actor's input schema and details dynamically using mcpc:
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```bash
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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"
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```
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Replace `ACTOR_ID` with the selected Actor (e.g., `apify/facebook-followers-following-scraper`).
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This returns:
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- Actor description and README
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- Required and optional input parameters
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- Output fields (if available)
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### Step 3: Ask User Preferences
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Before running, ask:
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1. **Output format**:
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- **Quick answer** - Display top few results in chat (no file saved)
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- **CSV** - Full export with all fields
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- **JSON** - Full export in JSON format
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2. **Number of results**: Based on character of use case
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### Step 4: Run the Script
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**Quick answer (display in chat, no file):**
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```bash
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node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
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--actor "ACTOR_ID" \
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--input 'JSON_INPUT'
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```
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**CSV:**
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```bash
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node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
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--actor "ACTOR_ID" \
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--input 'JSON_INPUT' \
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--output YYYY-MM-DD_OUTPUT_FILE.csv \
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--format csv
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```
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**JSON:**
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```bash
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node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
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--actor "ACTOR_ID" \
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--input 'JSON_INPUT' \
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--output YYYY-MM-DD_OUTPUT_FILE.json \
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--format json
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```
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### Step 5: Summarize Findings
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After completion, report:
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- Number of audience members/profiles analyzed
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- File location and name
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- Key demographic insights
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- Suggested next steps (deeper analysis, segmentation)
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## Error Handling
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`APIFY_TOKEN not found` - Ask user to create `.env` with `APIFY_TOKEN=your_token`
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`mcpc not found` - Ask user to install `npm install -g @apify/mcpc`
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`Actor not found` - Check Actor ID spelling
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`Run FAILED` - Ask user to check Apify console link in error output
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`Timeout` - Reduce input size or increase `--timeout`
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