Ghost Browser — AI-Powered Browser Automation

The browser moves on its own. No human needed.

GitHub: https://github.com/aiagentwithdhruv/ghost-browser Path: Social-Media-Agent-1.0/browser-automation/ Stack: Python 3, Playwright, OpenAI API

What It Does

Automates any browser action with human-like behavior — LinkedIn posting, engagement, job applications, web scraping, stats tracking, and visual demos.

Schema

Inputs

Name	Type	Required	Description
`LINKEDIN_LI_AT`	string	For LinkedIn	LinkedIn `li_at` cookie from DevTools
`TWITTER_AUTH_TOKEN`	string	For Twitter	Twitter auth_token cookie
`TWITTER_CT0`	string	For Twitter	Twitter ct0 cookie
`YOUTUBE_API_KEY`	string	For YouTube	Google Cloud API key (free)
`OPENAI_API_KEY`	string	For AI comments	GPT-4o-mini for comment/cover letter generation

Outputs

Name	Type	Description
LinkedIn post	Action	Published post with optional image
Feed data	JSON	Posts from LinkedIn feed with author, content, URN
Job listings	JSON	Jobs from LinkedIn/Indeed with title, company, description
Scraped data	JSON/CSV	Data from any website (smart/full/selector modes)
Stats	JSON + MD	Followers, views, connections across all platforms
Screenshots	PNG	Any URL, full page or element

Credentials

Service	How to Get
LinkedIn li_at	DevTools → Application → Cookies → linkedin.com
Twitter auth_token + ct0	DevTools → Application → Cookies → x.com
YouTube API	Google Cloud Console → YouTube Data API v3 (FREE)
OpenAI	platform.openai.com → API Keys

Cost

Component	Cost
Playwright/Chromium	Free
YouTube API	Free (10K units/day)
OpenAI (comments)	~$0.01 per comment
LinkedIn/Twitter	Free (cookie auth)

Scripts Reference

Script	What It Does	Example Command
`linkedin_engage.py`	LinkedIn CLI — post, feed, engage, apply, connect	`python3 linkedin_engage.py post --text "Hello" --image photo.jpg --visible`
`universal_scraper.py`	Scrape any website with 6 presets	`python3 universal_scraper.py indeed --query "AI engineer" --output jobs.json`
`stats_tracker.py`	Pull stats from all platforms	`python3 stats_tracker.py --notify`
`demo_wow.py`	6-stage visual demo (viral)	`python3 demo_wow.py`
`monkeytype_flex.py`	Speed typing demo (412 WPM)	`python3 monkeytype_flex.py`
`job_research.py`	Browse AI jobs on LinkedIn + Indeed	`python3 job_research.py`
`screenshot_tool.py`	Screenshot any URL	`python3 screenshot_tool.py --url "https://example.com"`

Architecture

human_behavior.py          ← Anti-detection layer
    ↓
base_browser.py            ← Playwright wrapper (cookie auth, context manager)
    ↓
├── linkedin_browser.py    ← LinkedIn: post, like, comment, apply, connect
├── linkedin_scraper.py    ← LinkedIn: followers, connections, analytics
├── twitter_scraper.py     ← Twitter: followers, impressions
├── youtube_stats.py       ← YouTube API (no browser)
├── universal_scraper.py   ← Any website (6 presets)
└── screenshot_tool.py     ← Screenshots
    ↓
├── linkedin_engage.py     ← CLI for LinkedIn
├── stats_tracker.py       ← Master orchestrator
├── demo_wow.py            ← Viral demo
└── job_research.py        ← Job market research

Human-Like Behavior Rules

Behavior	Implementation
Typing	40-55 WPM, char-by-char, 3-5% typo rate with backspace correction
Delays	Gaussian distribution (not uniform) — clusters around midpoint
Scrolling	Sinusoidal speed curve — slow start, fast middle, slow end
Clicking	Random offset from center (not dead-center like bots)
Reading	Wait time proportional to word count
Breaks	30-120 sec pause every 15-25 actions
Viewport	Random from pool: 1440x900, 1920x1080, 1536x864, etc.

LinkedIn Post Flow

1. Navigate to feed
2. Click "Start a post"
3. Find Quill editor (contenteditable div)
4. Short posts (<200 chars) → human_type with typos
   Long posts (>200 chars) → insert_text (paste)
5. Attach image → file input upload
6. Click "Next" (LinkedIn image editor step)
7. Click "Post" → confirmed

Composable With

Skill	How
`scrape-leads`	Scrape → enrich with ghost-browser LinkedIn data
`instantly-campaigns`	Scrape leads → cold email
`gmaps-leads`	Google Maps preset in universal_scraper
`cross-niche-outliers`	Research content → auto-post to LinkedIn
`upwork-apply`	Job research data feeds Upwork proposals
`send-telegram`	Stats tracker sends notifications

Revenue Use Cases

Use Case	Revenue
LinkedIn automation service	$500-2000/mo per client
Web scraping gigs (Fiverr/Upwork)	$200-1000 per project
LinkedIn ghostwriting + auto-post	$500-1500/mo per client
AI job application bot	$50-200 per person
Lead generation (scrape → email)	$500-2000/mo per client

Quick Start

cd Social-Media-Agent-1.0/browser-automation
pip install -r requirements.txt
playwright install chromium
cp .env.example .env  # Add your cookies

# Run the viral demo
python3 demo_wow.py

# Post to LinkedIn
python3 linkedin_engage.py post --text "Hello world" --visible

# Scrape Indeed jobs
python3 universal_scraper.py indeed --query "AI engineer" --output jobs.json