Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Productivity
Linkedin - automation
LinkedIn automation — post (with image upload), comment (with @mentions), edit/delete comments, repost, read feed, analytics, like monitoring, engagement tracking, and content calendar with approval workflow. Uses Playwright with persistent browser profile. Use for any LinkedIn task including content strategy, scheduled publishing, engagement analysis, and audience growth.
skill openclawclawhub Free
LinkedIn automation — post (with image upload), comment (with @mentions), edit/delete comments, repost, read feed, analytics, like monitoring, engagement tracking, and content calendar with approval workflow. Uses Playwright with persistent browser profile. Use for any LinkedIn task including content strategy, scheduled publishing, engagement analysis, and audience growth.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/cc-webhook.py, scripts/linkedin.py, scripts/requirements.txt, scripts/lib/actions.py, scripts/lib/analytics.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.1
Provenance
- Publisher
- red777777
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
LinkedIn Automation
Author: Community Contributors ⚠️ DISCLAIMER — PERSONAL USE ONLY This skill is provided for personal, non-commercial use only. It automates your own LinkedIn account for personal productivity and engagement. Do NOT use this skill for spam, mass outreach, scraping other users' data, or any commercial automation service. Use responsibly and in accordance with LinkedIn's User Agreement. The author assumes no liability for misuse or account restrictions. Automate LinkedIn interactions via headless Playwright browser with a persistent session.
Prerequisites
Python 3.10+ with Playwright installed (pip install playwright && playwright install chromium) A logged-in LinkedIn browser session (persistent Chromium profile) Adjust paths in scripts/lib/browser.py to match your setup
Commands
CLI={baseDir}/scripts/linkedin.py # Check if session is valid python3 $CLI check-session # Read feed python3 $CLI feed --count 5 # Create a post (text only) python3 $CLI post --text "Hello world" # Create a post with image (handles LinkedIn's image editor modal automatically) python3 $CLI post --text "Hello world" --image /path/to/image.png # Comment on a post (supports @Mentions — see below) python3 $CLI comment --url "https://linkedin.com/feed/update/..." --text "Great insight @Betina Weiler!" # Edit a comment (match by text fragment) python3 $CLI edit-comment --url "https://..." --match "old text" --text "new text" # Delete a comment python3 $CLI delete-comment --url "https://..." --match "text to identify" # Repost with thoughts python3 $CLI repost --url "https://..." --thoughts "My take..." # Engagement analytics for recent posts python3 $CLI analytics --count 10 # Profile-level stats (followers, views) python3 $CLI profile-stats # Monitor your likes for new ones (for comment suggestions) python3 $CLI scan-likes --count 15 # Scrape someone's activity python3 $CLI activity --profile-url "https://linkedin.com/in/someone/" --count 5 All commands output JSON. Enable debug logging: LINKEDIN_DEBUG=1.
@Mentions
Comments support @FirstName LastName syntax. The skill: Types @FirstName → waits for typeahead dropdown Progressively types last name letter by letter if needed Clicks the match only if first+last name both match Falls back to plain text if person not found (returns mention_failed warning) Check mentions in the JSON result to see if mentions succeeded.
Like Monitor
The scan-likes command checks your recent likes/reactions activity and returns any new likes since the last check. State is persisted to avoid duplicate alerts. Ideal for cron/heartbeat integration: # In HEARTBEAT.md or cron job: python3 $CLI scan-likes → if new likes found → suggest comment for each
⚠️ Golden Rule
NEVER post, comment, repost, edit, or delete anything without EXPLICIT user approval. Always show the user exactly what will be posted and get a clear "yes" before executing. Read-only actions (feed, analytics, check-session, scan-likes) are safe to run freely.
Content Calendar (Scheduled Publishing)
Full approval-based publishing workflow with auto-posting. See references/content-calendar.md for setup. Webhook (scripts/cc-webhook.py): Receives approve/edit/skip from a frontend UI Auto-apply: Simple edits ("old text -> new text") applied instantly by webhook Agent processing: Complex edits flagged for AI-powered text rewriting Auto-post: Approved posts past their scheduled time are posted automatically via cron Image strategy: Real photos + AI-generated story overlays (not stock photos) # Start the webhook (or install as systemd service) python3 scripts/cc-webhook.py # Env vars for config: # CC_DATA_FILE=/path/to/cc-data.json # CC_ACTIONS_FILE=/path/to/actions.json # CC_WEBHOOK_PORT=8401
Content Strategy & Engagement
references/content-strategy.md — Hook formulas, post structure, posting times, hashtag strategy, 4-1-1 rule references/engagement.md — Algorithm signals, comment quality formula, rate limits, weekly routine references/dom-patterns.md — Known LinkedIn DOM patterns for troubleshooting references/content-calendar.md — Content calendar setup, data format, webhook API
Rate Limits
ActionDaily MaxWeekly MaxPosts2–310–15Comments20–30—Likes100—Connection requests30100
Setup
Install dependencies: pip install playwright && playwright install chromium Configure browser profile path in scripts/lib/browser.py (or set LINKEDIN_BROWSER_PROFILE env var) Log in to LinkedIn manually once (the session persists) Run python3 scripts/linkedin.py check-session to verify Learn your voice: Run python3 scripts/linkedin.py learn-profile — this scans your recent posts and comments to learn your tone, topics, language, and style. The agent uses this profile when suggesting comments/posts so they sound like you, not like a generic bot.
Voice & Style
On first setup, learn-profile analyzes your content and saves a style profile (~/.linkedin-style.json) containing: Language (de/en/mixed) Tone (casual / professional / professional-friendly) Emoji usage (heavy / moderate / minimal) Top hashtags you use Sample posts and comments for voice reference The agent should ALWAYS read this profile (get-style) before drafting any comment or post suggestion. Never impose a foreign voice — match the user's natural style.
Post Age Warning
CRITICAL: Before suggesting a comment on any post, check how old the post is: < 2 weeks: Safe to comment > 2 weeks: Warn the user explicitly ("⚠️ This post is X weeks old — commenting on old posts can look like bot behavior. Still want to?") > 1 month: Strongly discourage unless there's a specific reason Commenting on old posts makes it look like you're mining someone's history with a bot. Always flag post age.
Troubleshooting
Session expired: Log in again via browser profile Selectors broken: LinkedIn updates UI frequently — check references/dom-patterns.md and update scripts/lib/selectors.py Debug screenshots: Saved to /tmp/linkedin_debug_*.png on failure
Category context
Workflow acceleration for inboxes, docs, calendars, planning, and execution loops.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
4 Scripts1 Docs1 Files
- SKILL.md
- scripts/cc-webhook.py
- scripts/lib/actions.py
- scripts/lib/analytics.py
- scripts/linkedin.py
- scripts/requirements.txt