skills/claude-skills-open/skills/channels/linkedin-cdp/SKILL.md
--- name: linkedin-cdp description: LinkedIn CDP: Input-only automation (mouse, keyboard, screenshots). Zero DOM access. --- # LinkedIn CDP Automation > LinkedIn automation via Chrome DevTools Protocol. Input-only (mouse/keyboard/screenshots). Zero DOM access. ## When to use - "collect messages from linkedin" -> `LinkedInMessages` - "who messaged me on linkedin" -> `LinkedInMessages` - "write on linkedin" -> `LinkedInMessages.send_message()` - "find on linkedin" -> `LinkedInSearch` - "view pr
npx skillsauth add aaaaqwq/claude-code-skills skills/claude-skills-open/skills/channels/linkedin-cdpInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
LinkedIn automation via Chrome DevTools Protocol. Input-only (mouse/keyboard/screenshots). Zero DOM access.
LinkedInMessagesLinkedInMessagesLinkedInMessages.send_message()LinkedInSearchLinkedInProfileLinkedInConnectLinkedInConnect.screenshot_invitations()pip install websocket-client requests--remote-debugging-port=9222 (separate instance)| What | Path |
|------|------|
| Script | $HOME/linkedin-cdp/linkedin_cdp.py |
| Modules | $HOME/linkedin-cdp/linkedin_*.py |
| Rate limiter | $HOME/linkedin-cdp/rate_limiter.py |
| Screenshots | /tmp/li_screenshots/shot_*.jpg |
IMPORTANT: Use the binary path directly, NOT open -a 'Google Chrome'.
open -a on macOS opens a tab in existing Chrome instead of a separate instance.
/Applications/Google\ Chrome.app/Contents/MacOS/Google\ Chrome \
--remote-debugging-port=9222 \
'--remote-allow-origins=*' \
--user-data-dir="$HOME/chrome-debug-profile" \
"https://www.linkedin.com" > /dev/null 2>&1 &
Run in background (run_in_background: true), then verify:
sleep 3 && curl -s "http://localhost:9222/json/version"
--user-data-dir MUST differ from user's main Chrome profile$HOME/chrome-debug-profile persists login session between runsEvery session may have different window size / DPR. On first run, take a calibration screenshot and determine the coordinate mapping:
import sys, subprocess, time
sys.path.insert(0, '$HOME/linkedin-cdp')
from linkedin_cdp import LinkedInBot
bot = LinkedInBot()
bot.connect()
# Take calibration screenshot — returns file path
path = bot.take_screenshot()
print(path) # /tmp/li_screenshots/shot_0001.jpg
# Get image dimensions to determine DPR
result = subprocess.run(['sips', '-g', 'pixelWidth', '-g', 'pixelHeight', path],
capture_output=True, text=True)
print(result.stdout)
bot.close()
Then read the calibration screenshot with Read tool. Calculate:
Store the DPR for all subsequent coordinate calculations in this session.
All click_at(), _click() calls use CSS coordinates, not image pixels.
Formula: CSS_coord = image_pixel_coord / DPR
Typical Retina Mac (DPR=2, viewport ~1531x801):
import sys
sys.path.insert(0, '$HOME/linkedin-cdp')
from linkedin_cdp import LinkedInBot
bot = LinkedInBot()
bot.connect()
# All actions use CSS coordinates
bot.click_at(x, y) # click + screenshot
bot.type_text("text") # type with human-like delays
bot.scroll_wheel(delta_y=500) # scroll (keyword arg only!)
bot.take_screenshot() # returns file path (JPEG)
bot.navigate_to(url) # navigate + auto reconnect
bot.reconnect_to_tab() # reconnect WebSocket after page change
bot.close()
These modal/dialog coordinates are consistent across sessions at the same viewport size. Recalibrate if window size changes.
After clicking "Connect" on a profile:
| Element | CSS (x, y) | Notes | |---------|-----------|-------| | "Add a note" button | (751, 239) | White/outline button | | "Send without a note" button | (911, 239) | Blue button | | Note text field (click to focus) | (752, 259) | After clicking "Add a note" | | "Send" button (with note) | (968, 393) | Blue, active after typing | | "Cancel" button | (889, 393) | |
| Element | CSS (x, y) | Notes | |---------|-----------|-------| | "Connect" button | (~270, 467-499) | y varies by profile layout (banner height, etc.) | | "Message" button | (~383, 467-499) | Next to Connect |
/messaging/ — conversation list on left, active thread on right.
| Element | CSS (x, y) | Notes | |---------|-----------|-------| | "Write a message..." text field | (715, 604) | Click to focus, then type_text() | | Send button | (885, 724) | Active (blue) only after typing |
/mynetwork/invitation-manager/ — lists received/sent invitations.
| Element | CSS (x, y) | Notes | |---------|-----------|-------| | "Accept" button (first invite) | (~920, 274) | Approximate — verify via screenshot | | "Ignore" button (first invite) | (~838, 274) | Next to Accept | | "Received" / "Sent" tabs | (~265, 142) / (~350, 142) | Top of page |
| Element | CSS (x, y) | Notes | |---------|-----------|-------| | First result name | (~305, 155) | Approximate — always verify via screenshot | | Second result name | (~305, 280) | Approximate — positions shift with ads/banners |
LinkedInBot (linkedin_cdp.py) -- base class
|-- CDP core: connect(), _send(), close(), reconnect_to_tab()
|-- Mouse: _bezier(), _human_path(), _move_to(), _click(), _maybe_fake_hover()
|-- Keyboard: type_text(), press_key()
|-- Scroll: scroll_wheel()
|-- Screenshot: take_screenshot() -> path, take_screenshot_base64(), save_screenshot()
|-- Navigation: navigate_to(), wait_for_page()
|-- Convenience: click_at(x,y) -> screenshot, scroll_and_screenshot()
|
+-- LinkedInMessages (linkedin_messages.py)
+-- LinkedInSearch (linkedin_search.py)
+-- LinkedInProfile (linkedin_profile.py)
+-- LinkedInConnect (linkedin_connect.py)
| File | Class | Key Methods |
|------|-------|-------------|
| linkedin_cdp.py | LinkedInBot | click_at(), type_text(), scroll_wheel(), take_screenshot() -> path, take_screenshot_base64(), navigate_to() |
| linkedin_messages.py | LinkedInMessages | screenshot_conversations(), open_conversation(), send_message(), collect_screenshots() |
| linkedin_search.py | LinkedInSearch | search_people(), search_companies(), next_page() |
| linkedin_profile.py | LinkedInProfile | view_profile(), screenshot_full_profile(), scroll_to_section() |
| linkedin_connect.py | LinkedInConnect | view_profile(), send_connection_note(), screenshot_invitations(), accept_invitation() |
| rate_limiter.py | RateLimiter | can_search(), can_view_profile(), wait_if_needed() |
import sys, time
sys.path.insert(0, '$HOME/linkedin-cdp')
from linkedin_cdp import LinkedInBot
bot = LinkedInBot()
bot.connect()
# 1. Search
bot.navigate_to('https://www.linkedin.com/search/results/people/?keywords=Name%20Company')
time.sleep(4)
bot.reconnect_to_tab()
time.sleep(2)
# take_screenshot() returns file path — read with Read tool to find coordinates
# 2. Click profile (coordinates from screenshot / DPR)
path = bot.click_at(305, 155) # first result — verify from screenshot!
time.sleep(4)
bot.reconnect_to_tab()
# Read path with Read tool to verify correct profile
# 3. Click Connect (~270, 467-499 — verify from screenshot)
bot.click_at(270, 499)
time.sleep(2)
# Modal appears
# 4. Click "Add a note" (fixed coordinate)
bot.click_at(751, 239)
time.sleep(1.5)
# 5. Click text field + type note
bot._click(752, 259)
time.sleep(0.5)
bot.type_text("Hi Name, personalized note here...")
time.sleep(1)
# 6. Click Send (fixed coordinate)
bot.click_at(968, 393)
# Done — verify "Pending" status + "Invitation sent" toast
bot.close()
from linkedin_messages import LinkedInMessages
lm = LinkedInMessages()
lm.connect()
path = lm.screenshot_conversations()
# path = '/tmp/li_screenshots/shot_NNNN.jpg' — read with Read tool
path = lm.open_conversation(200, 350) # coordinates from screenshot
# Read path with Read tool
lm.close()
import time
from linkedin_profile import LinkedInProfile
prof = LinkedInProfile()
prof.connect()
prof.navigate_to('https://linkedin.com/in/username')
time.sleep(4)
prof.reconnect_to_tab()
paths = [prof.take_screenshot()]
for _ in range(4):
prof.scroll_wheel(delta_y=500)
time.sleep(1.5)
paths.append(prof.take_screenshot())
# paths = ['/tmp/li_screenshots/shot_0001.jpg', ...] — read each with Read tool
prof.close()
| Problem | Solution |
|---------|----------|
| WebSocketConnectionClosedException after navigate | Call reconnect_to_tab() — page change breaks WebSocket |
| Click misses target | Verify DPR: image_pixels / DPR = CSS coords. Re-run calibration. |
| screenshot_full_profile() crashes | Use manual navigate + reconnect + scroll loop (see View Profile example) |
| scroll_wheel() TypeError | Use keyword arg only: scroll_wheel(delta_y=500), NOT positional args |
| Chrome opens tab in existing browser | Use binary path directly, NOT open -a 'Google Chrome' |
| CDP port conflict | Change --remote-debugging-port=9223 and update CDP_PORT in linkedin_cdp.py |
| Modal coordinates wrong | Window resized? Re-run calibration. Fixed coords assume viewport ~1531x801. |
scroll_wheel() takes delta_y keyword arg only. Not positional.navigate_to() or page-changing click, always reconnect_to_tab().sys.path.insert(0, '$HOME/linkedin-cdp') before imports./tmp/li_screenshots/shot_*.jpg — read them with Read tool. Old files auto-cleaned (keeps last 50).| Action | Conservative | Moderate | |--------|-------------|----------| | Profile views | 50 | 100 | | Searches | 20 | 50 | | Connection requests | 15 | 25 | | Messages sent | 30 | 50 |
Zero DOM access — NEVER Runtime.evaluate, querySelector, innerText.
Screenshot-based reading — Page.captureScreenshot (JPEG, quality 80) saved to files, not base64 in memory.
Human-like mouse — unique Bezier curves, tremor, overshoot, micro-pauses, speed variation.
Real Chrome — not headless. Normal fingerprint.
Rate limiting — built-in daily caps.
Human-in-the-loop — Claude reads screenshots, adds natural irregularity.
Runtime.evaluate or CDP Runtime domain — #1 way bots get caughtAfter sending a connection request or message, ALWAYS log to CRM:
companies.csv (if new)people.csv (if new)leads.csv (stage=new, source=linkedin, source_direction=outbound)activities.csv with the exact message text in notes field:
type: outreachchannel: linkedindirection: outboundsubject: "LinkedIn connection request with note" (or "LinkedIn message")notes: the full text of the message sentDo NOT skip step 4. The message text must be preserved in CRM for follow-up context.
add-lead — add found contacts to CRMupdate-lead — update lead status after outreachlog-activity — log activity to activities.csvemail-send-bulk — follow up via email after LinkedIn connecttesting
通用自媒体文章自动发布工具。支持百家号、搜狐号、知乎、微信公众号、小红书、抖音号六个平台的自动化发布流程。使用Playwright自动化实现平台导航和发布,支持通过storageState管理Cookie实现账号切换。
development
# SKILL.md - Model Configuration Status (mcstatus) ## 触发条件 - `/mcstatus` 命令 - 用户询问模型配备、模型配置、model status、模型列表等 ## 功能 实时生成 Agent + Cron 的模型配置报告,展示当前所有 agent 的主模型/fallback链和所有 cron 任务的模型分配。 ## 执行步骤 ### Step 1: 收集 Agent 模型配置 读取各 agent 的 models.json 获取主模型和 fallback 链: ```bash for agent in main ops code quant data research content market finance pm law product sales batch; do config=$(cat ~/.openclaw/agents/$agent/agent/models.json 2>/dev/null) if [ -n "$config" ]; then echo "=== $agent
tools
MCP 服务器智能管理助手。自动检测 MCP 可用性、智能开关、功能问答,提供人性化的 MCP 管理体验。
tools
从GitHub搜索并自动安装配置MCP(Model Context Protocol)服务器工具到Claude配置文件。当用户需要安装MCP工具时触发此技能。工作流程:搜索GitHub上的MCP项目 -> 提取npx配置 -> 添加到~/.claude.json -> 处理API密钥(如有)。