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AI-powered browser automation with human-like behavior — LinkedIn, Twitter, Indeed, GMaps, GitHub, HackerNews, MonkeyType
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Integrating Chrome DevTools and browser automation via MCP for live UI inspection, screenshot-to-code workflows, and visual debugging. Bridges the gap between design and implementation.
Raw mechanical interfaces fusing Swiss typographic print with military terminal aesthetics. Rigid grids, extreme type scale contrast, utilitarian color, analog degradation effects. For data-heavy dashboards, portfolios, or editorial sites that need to feel like declassified blueprints.
Use when the user says /rise, "good morning", "let's start the day", or wants their morning consciousness routine. Identifies the Floor from natural-language check-in (does NOT ask the user to name a floor), runs body movement scaled to cycle phase or feeling, recommends top 1-3 priorities from configured to-do files, derives a daily intention. Pairs with /journal at night for accountability. Do NOT use for evening reflection (use /journal), pattern detection (use /patterns), or workout prescription (use /coach for the full session — /rise only handles the post-wake body wake-up flow).
FLOW framework integration — evidence-led SEO using the Find → Leverage → Optimize → Win loop. Surfaces stage-specific AI prompts from the FLOW knowledge base (41 prompts, CC BY 4.0). Use when user says "FLOW", "FLOW framework", "seo flow", "evidence-led SEO", "find leverage optimize win", or wants stage-specific SEO prompts.
Index and search culture documentation
Advanced Scrum Master skill for data-driven agile team analysis and coaching. Use when the user asks about sprint planning, velocity tracking, retrospectives, standup facilitation, backlog grooming, story points, burndown charts, blocker resolution, or agile team health. Runs Python scripts to analyse sprint JSON exports from Jira or similar tools: velocity_analyzer.py for Monte Carlo sprint forecasting, sprint_health_scorer.py for multi-dimension health scoring, and retrospective_analyzer.py for action-item and theme tracking. Produces confidence-interval forecasts, health grade reports, and improvement-velocity trends for high-performing Scrum teams.
| name | ghost-browser |
| description | AI-powered browser automation with human-like behavior — LinkedIn, Twitter, Indeed, GMaps, GitHub, HackerNews, MonkeyType |
| argument-hint | --agents linkedin,indeed --visible |
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
Automates any browser action with human-like behavior — LinkedIn posting, engagement, job applications, web scraping, stats tracking, and visual demos.
| 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 |
| 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 |
| 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 |
| Component | Cost |
|---|---|
| Playwright/Chromium | Free |
| YouTube API | Free (10K units/day) |
| OpenAI (comments) | ~$0.01 per comment |
| LinkedIn/Twitter | Free (cookie auth) |
| Script | What It Does | Example Command |
|---|---|---|
orchestrator.py | Multi-agent orchestrator (8 agents, 5 combos) | python3 orchestrator.py --demo --visible |
ghost_mcp.py | MCP server (10 tools for any AI agent) | python3 ghost_mcp.py (stdio transport) |
multi_context.py | Isolated browser session manager | Used by orchestrator |
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" |
human_behavior.py ← Anti-detection layer (mouse drift, idle, warmup)
↓
base_browser.py ← Playwright wrapper (cookie auth, context manager)
multi_context.py ← Isolated browser sessions (multiple contexts, 1 process)
↓
orchestrator.py ← 8 agents, 5 combos, CLI
├── agent_linkedin_feed / agent_linkedin_engage
├── agent_scrape_indeed / agent_scrape_gmaps
├── agent_twitter_trending (cookie auth: TWITTER_AUTH_TOKEN + TWITTER_CT0)
├── agent_monkeytype / agent_github_trending / agent_hacker_news
└── run_orchestrator() → parallel execution in isolated contexts
↓
ghost_mcp.py ← MCP server (10 tools) for Claude/Cursor/Codex
↓
├── 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 ← Stats + Telegram notifications
├── demo_wow.py ← Viral demo
└── job_research.py ← Job market research
| Agent | Description |
|---|---|
linkedin-feed | Scroll feed, extract posts |
linkedin-engage | Like posts with human behavior |
indeed | Scrape Indeed job listings |
gmaps | Scrape Google Maps businesses |
monkeytype | Speed typing demo (~400 WPM) |
github | Browse GitHub trending repos |
hackernews | Read top Hacker News stories |
twitter | Scrape X.com trending/search (cookie auth) |
| Combo | Agents |
|---|---|
demo | monkeytype, github, hackernews |
research | linkedin-feed, indeed, github, twitter |
lead-gen | linkedin-feed, gmaps, indeed |
social | linkedin-feed, twitter, hackernews |
full | all 6 non-demo agents |
{
"mcpServers": {
"ghost-browser": {
"command": "python3",
"args": ["/path/to/ghost_mcp.py"],
"env": { "LINKEDIN_LI_AT": "...", "OPENAI_API_KEY": "sk-..." }
}
}
}
Tools: linkedin_feed, linkedin_post, linkedin_engage, scrape_url, scrape_indeed, scrape_gmaps, scrape_twitter, typing_demo, screenshot, multi_run
| 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. |
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
| 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 |
| 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 |
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