From bungkust-skills
Scrapes Threads, Instagram, TikTok profiles via Python scripts and curl, analyzes engagement metrics, posting patterns, content themes, and viral outliers for audits and content strategies.
npx claudepluginhub bungkust/bungkust-skillsThis skill uses the workspace's default tool permissions.
Unified skill: audit + learn + strategy. One skill, any platform.
Tracks and analyzes content performance across Instagram, YouTube, LinkedIn, Twitter/X, Reddit using anysite MCP. Measures engagement metrics, identifies top posts, benchmarks strategies.
Analyzes audience demographics, engagement patterns, and behavior on Facebook, Instagram, YouTube, TikTok using Apify Actors and mcpc CLI. Useful for extracting social media insights via targeted scrapers.
Tracks engagement metrics, ROI, and content performance across Instagram, Facebook, YouTube, TikTok using Apify Actors. Guides scraper selection, schema fetching, and Node.js-based analysis workflows.
Share bugs, ideas, or general feedback.
Unified skill: audit + learn + strategy. One skill, any platform.
User: "bedah akun @username"
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Step 1: SCRAPE (1 call)
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Step 2: ANALYZE (inline, no extra calls)
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Step 3: OUTPUT (structured report)
cd ~/threads-scraper && source venv/bin/activate
python3 src/scraper.py -u USERNAME --limit 50
Output: ~/threads-scraper/output/threads_YYYYMMDD_HHMMSS.json
curl -s -L \
-H "User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36" \
-H "X-IG-App-ID: 936619743392459" \
"https://www.instagram.com/api/v1/users/web_profile_info/?username=USERNAME"
browser_navigate(url="threads.com/@username")
browser_snapshot(full=true)
browser_vision(question="Analyze profile and visible posts")
From scraped JSON, compute ALL metrics in ONE execute_code block:
import json
from collections import Counter
from datetime import datetime
with open("path/to/scraped.json") as f:
posts = json.load(f)
# === ENGAGEMENT STATS ===
likes = [p.get('like_count', 0) for p in posts]
replies = [p.get('reply_count', 0) for p in posts]
# Report: avg, max, min, total
# === POSTING FREQUENCY ===
dates = sorted([p['created_at'] for p in posts])
# Calculate: posts/day, avg gap, max gap, day distribution
# === CONTENT THEMES ===
# Categorize posts by keywords
# Compare engagement BY THEME (most actionable insight!)
# === STYLE PATTERNS ===
# Count: emoji %, hashtag %, question %, CTA %, link %
# === CONTENT LENGTH ===
lengths = [len(p.get('text', '')) for p in posts]
# avg, max, min
# === VIRAL OUTLIERS ===
threshold = sum(likes) / len(likes) * 3 # 3x average
viral = [p for p in posts if p.get('like_count', 0) > threshold]
## 🔍 AUDIT: @{username}
### 📊 SNAPSHOT
| Metric | Value |
|--------|-------|
| Followers | X |
| Posts analyzed | X |
| Avg engagement | X |
| Top content type | X |
### 📈 ENGAGEMENT (Full Breakdown)
| Metric | Avg | Max | Best Post |
|--------|-----|-----|-----------|
| Likes | X | X | [topic] |
| Replies | X | X | [topic] |
### 📅 POSTING PATTERNS
| Metric | Value |
|--------|-------|
| Frequency | X posts/week |
| Best day | [day] |
| Biggest gap | X days |
### 🎯 CONTENT THAT WORKS
| Theme | Posts | Avg Likes | Win Rate |
|-------|-------|-----------|----------|
| [theme1] | X | X | X% |
### ✅ STRENGTHS
### ⚠️ IMPROVEMENTS
### 🎯 TOP 3 PRIORITIES
## 📖 BELAJAR: @{username} tentang [TOPIK]
### 🔑 PRINSIP UTAMA
[1 kalimat prinsip besar]
### 📘 Pelajaran 1: "[Judul]"
> Quote asli
**Ilmunya:** [poin]
**Praktek:** [action item]
### 📘 Pelajaran 2: ...
### 🎯 RINGKASAN: N Langkah
[Tabel actionable steps]
## 🎯 CONTENT SERIES: [Nama Series]
### COMPARISON
| Element | Reference | Your Style | Adaptation |
|---------|-----------|------------|------------|
| Tone | X | Y | Z |
### SERIES FORMAT
- Structure: [thread/single]
- Cadence: [frequency]
- Hashtags: [list]
### READINESS CHECK
| Item | Status |
|------|--------|
| Materials ready | ✅/❌ |
| Visual content | ✅/❌ |
| Bio aligned | ✅/❌ |
### BATCH POSTS (3-5)
[Generated posts in approved format]
If user has multiple accounts: