功能描述

Analyze Instagram profiles and posts with detailed engagement metrics, view tracking, follower ratios, and Reels-focused analytics with JSON/CSV export.

使用说明 (SKILL.md)

Instagram Analyzer

Name: Instagram Analyzer
Author: tevfikgulep

A comprehensive Instagram profile and post analysis tool with engagement metrics, view tracking, and Reels-focused analytics.

---
name: instagram-analyzer
description: Analyze Instagram profiles and posts with engagement metrics, view counts, follower ratios, and Reels analytics.
emoji: 📊
version: 1.0.0
author: Sencer
tags:
  - instagram
  - analytics
  - engagement
  - reels
  - influencer
metadata:
  clawdbot:
    requires:
      bins:
        - python3
        - chromium
      pip:
        - playwright
        - beautifulsoup4
        - lxml
    config:
      stateDirs:
        - data/output
        - data/profiles
        - data/posts
      outputFormats:
        - json
        - csv
---

🎯 Features

📊 Single Post Analysis

✅ Like count
✅ Comment count
✅ Save count
✅ View count (Reels)
✅ Follower count
✅ View-to-Follower ratio (%)
✅ Time posted (hours/days ago)

👤 Profile Analysis

✅ Minimum 60 posts analyzed
✅ Reels-focused analytics
✅ All Reels links extraction
✅ Engagement rate calculations
✅ JSON/CSV export

🔧 Technical

🌐 Browser simulation with Playwright
🛡️ Stealth mode (human behavior)
📁 Structured JSON/CSV output
⚡ Batch processing support

🚀 Usage

Profile Analysis (Default: Reels Only! 🎯)

# Full profile analysis - REELS FOCUS (default behavior)
analyze-profile "username"

# With custom post count
analyze-profile "username" --posts 60

# All posts (including regular posts)
analyze-profile "username" --include-posts

Single Post Analysis

# Analyze a Reel/post URL
analyze-post "https://www.instagram.com/reel/ABC123xyz/"

# With JSON output
analyze-post "https://www.instagram.com/reel/ABC123xyz/" --output json

📊 Output Examples

Single Post Response

{
  "post_type": "reel",
  "url": "https://www.instagram.com/reel/ABC123xyz/",
  "username": "example_user",
  "metrics": {
    "views": 125000,
    "likes": 8542,
    "comments": 312,
    "saves": 892,
    "followers": 125000,
    "shares": 156
  },
  "ratios": {
    "view_to_follower_percent": 100.0,
    "like_to_view_percent": 6.83,
    "comment_to_view_percent": 0.25,
    "save_to_view_percent": 0.71
  },
  "timing": {
    "posted_at": "2026-02-11T14:30:00",
    "time_ago": "6 hours ago",
    "age_hours": 6
  }
}

Profile Analysis Response

{
  "profile": {
    "username": "example_user",
    "full_name": "Example User",
    "followers": 125000,
    "following": 1500,
    "posts_count": 450,
    "is_verified": false
  },
  "analysis_summary": {
    "total_posts_analyzed": 60,
    "reels_analyzed": 45,
    "analysis_mode": "reels_only",
    "total_views": 5420000,
    "average_views": 120444,
    "average_engagement_rate": 8.2,
    "top_reels": [...],
    "reels_links": [
      "https://www.instagram.com/reel/ABC123/",
      "https://www.instagram.com/reel/DEF456/",
      ...
    ]
  },
  "engagement_breakdown": {
    "avg_likes": 8542,
    "avg_comments": 312,
    "avg_saves": 892,
    "engagement_rate": 7.8
  }
}

📈 Engagement Metrics Explained

Metric	Formula	Interpretation
View Rate	(Views / Followers) × 100	How many followers actually watched
Engagement Rate	((Likes + Comments + Saves) / Views) × 100	Overall audience interaction
Like Rate	(Likes / Views) × 100	Content appreciation
Save Rate	(Saves / Views) × 100	Content value indicator

⚙️ Configuration

Edit config/analyzer_config.json:

{
  "scraper": {
    "headless": false,
    "min_followers": 1000,
    "posts_to_analyze": 60,
    "scroll_pause": 2,
    "timeout": 30000
  },
  "browser": {
    "stealth_mode": true,
    "human_behavior": true,
    "user_agent": "Mozilla/5.0 (iPhone; CPU iPhone OS 16_0 like Mac OS X)"
  },
  "output": {
    "default_format": "json",
    "save_reels_links": true,
    "export_csv": true
  }
}

📁 File Outputs

Profile data: data/profiles/{username}.json
Post analysis: data/posts/{post_id}.json
Batch results: data/output/batch_{timestamp}.json
Reels links: data/output/{username}_reels.txt

🔧 Troubleshooting

Login Required

Some metrics require login (view count, saves)
Configure Instagram credentials in .env

Rate Limiting

Increase scroll_pause in config
Reduce batch size
Use multiple accounts

Missing Data

Check if account is private
Verify post exists and is accessible
Instagram may hide some metrics

📝 Requirements

Python 3.8+
Playwright
Chromium browser
BeautifulSoup4
lxml parser

安全使用建议

This skill appears to implement an Instagram scraper using Playwright and stores results under data/*. However: (1) the registry metadata does not declare the runtime binaries and credentials the SKILL.md and config expect — confirm you will need python3, Playwright, and Chromium and be prepared to run `playwright install chromium`. (2) Some metrics require Instagram login; the config and README mention using a .env for credentials. Only provide real Instagram credentials if you trust the code and its origin — consider using a throwaway/test account. (3) The script writes scraped data and possibly credentials to local files (data/). Inspect the full script locally (note: the provided script in the package was truncated in the review sample) to ensure there are no hidden network endpoints or exfiltration steps before running. (4) Running scrapers can violate Instagram's terms of service and may trigger rate limits or blocks; use rate-limiting settings and consider isolation (container/VM) when testing. If you plan to install, ask the publisher to fix the metadata to list required binaries and to explicitly document how credentials are used and stored.

功能分析

Type: OpenClaw Skill Name: instagram-analyzer Version: 1.0.0 The skill bundle is classified as suspicious due to multiple vulnerabilities. The `scripts/instagram_analyzer.py` script is vulnerable to path traversal, as user-supplied usernames are directly used in constructing output file paths (e.g., `data/profiles/{username}_{timestamp}.json`), allowing arbitrary file writes. Additionally, Instagram credentials configured in `config/analyzer_config.json` are loaded into memory but never used for login, exposing sensitive data unnecessarily. The script also navigates to user-supplied URLs via Playwright, which could be exploited for browser-based attacks or internal network scanning.

能力评估

ℹ Purpose & Capability

The name, SKILL.md, and the Python script are coherent: they implement browser-based scraping (Playwright) to analyze Instagram posts/profiles. However, the registry metadata advertised no required binaries or env vars while SKILL.md lists python3, chromium, and Playwright, and the config file contains instagram username/password fields. That metadata mismatch is unexpected and should be clarified.

✓ Instruction Scope

Runtime instructions limit activity to browser simulation of Instagram pages, local scraping, and writing structured JSON/CSV outputs into data/ directories. The SKILL.md does ask users to place Instagram credentials in a .env for metrics that require login; otherwise the instructions do not attempt arbitrary file reads or external network reporting beyond visiting Instagram pages.

✓ Install Mechanism

There is no install spec in the registry (instruction-only), and the included requirements.txt references standard packages (playwright, beautifulsoup4, lxml, requests). No downloads from suspicious URLs or archive extraction were observed. Note: installing Playwright will download browser binaries (normal for Playwright), so users should run that step from an environment they trust.

⚠ Credentials

The skill implicitly needs Instagram credentials to retrieve some metrics (SKILL.md and config/analyzer_config.json reference username/password and .env), but the registry lists no required env vars or primary credential. Requesting or storing Instagram credentials is proportionate to the feature set, but the lack of declared credential requirements in metadata is an incoherence and a potential risk: the skill will ask for secrets without that being obvious in the registry. Also the script writes scraped data and potentially credentials to local data files; users should understand where sensitive data is stored.

✓ Persistence & Privilege

The skill is not always-enabled and does not request elevated system-wide privileges. It writes outputs under data/ (data/profiles, data/posts, data/output), which is reasonable for the stated purpose. Autonomous invocation is allowed (platform default) but not combined here with any other high-risk flags.

版本历史

v1.0.0

- Initial release of Instagram Analyzer. - Analyze Instagram profiles and posts: engagement metrics, view counts, ratios, and Reels analytics. - Supports single post and profile analysis, with Reels-focused default. - Outputs results in JSON and CSV formats. - Technical features include Playwright-based browser simulation, stealth (human-like) mode, and batch processing. - Customizable configuration for scraping, browser behavior, and output.

元数据

Slug instagram-analyzer

版本 1.0.0

许可证 —

累计安装 5

当前安装数 4

历史版本数 1

常见问题