A browser automation skill for drafting, preparing, and publishing LinkedIn feed posts through the OpenClaw agent ecosystem.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install linkedin-post-openclaw-browser
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install linkedin-post-openclaw-browser using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is LinkedIn Post Automation Skill?
This skill enables developers and content creators to bridge the gap between AI-generated content and professional social media presence. By leveraging the Openclaw Skills framework, it automates the repetitive parts of the LinkedIn posting workflow while maintaining a strict safety-first approach. It uses real browser automation to navigate the LinkedIn feed, interact with the share modal, and populate content exactly as a human would, ensuring high reliability and compliance with platform layouts.
Unlike traditional API-based posting which can be restrictive, this skill utilizes a browser-based flow. This allows the AI agent to verify link unfurls, check formatting, and ensure the UI is in a ready state before any action is taken. It is designed specifically for feed posts, providing a standardized path for moving from a text draft to a live social update within the Openclaw Skills environment.
LinkedIn Post Automation Skill Use Cases
- Automating the distribution of AI-generated technical updates or blog summaries to LinkedIn.
- Standardizing recurring social media posting workflows within a developer relations or marketing team.
- Preparing draft posts for manual review and final approval in the browser before going live.
- Integrating LinkedIn publishing into a broader automated content pipeline powered by Openclaw Skills.
How LinkedIn Post Automation Skill Works
- The user finalizes the post copy with the AI agent to ensure tone, hashtags, and structure are correct.
- The skill validates the local environment, checking for the necessary gateway token and an active browser profile.
- A Python helper script triggers the OpenClaw browser automation to navigate to the LinkedIn feed with the share modal active.
- The script performs a snapshot of the page to identify the composer textbox and fills it with the finalized content.
- The system allows the user to verify the preview, ensuring that links have unfurled correctly and the layout is as expected.
- Upon explicit user approval, the skill executes the publish command to finalize the post.
LinkedIn Post Automation Skill Setup
To get started with this skill, ensure the OpenClaw CLI is installed and your browser is logged into LinkedIn.
- Configure your gateway token:
export OPENCLAW_GATEWAY_TOKEN="your_token_here"
- Prepare your post content in a text file and use the helper script to stage the post:
python3 scripts/linkedin_post.py --content-file /tmp/linkedin_post.txt
- To publish once approved, add the publish flag:
python3 scripts/linkedin_post.py --content-file /tmp/linkedin_post.txt --publish
LinkedIn Post Automation Skill Data Schema & Taxonomy
The skill manages data through the following schema to ensure consistency across the Openclaw Skills ecosystem:
| Component | Description | Format |
|---|---|---|
| Content File | The raw text or Markdown file containing the final post body | .txt or .md |
| Config File | Stores gateway tokens and browser profile paths for persistence | openclaw.json |
| Gateway Token | Security credential for authenticating with the Openclaw Skills backend | Env Var or JSON |
| Browser Profile | The persistent storage directory containing the authenticated LinkedIn session | Directory Path |
LinkedIn Post Automation Skill Advanced Features
- Multi-stage safety checks that strictly separate content preparation from the final publishing action.
- Dynamic DOM element discovery through real-time snapshots, preventing breakage from LinkedIn UI updates.
- Support for piping content directly from standard input (stdin) for high-velocity CLI-driven workflows.
- Automated verification of link unfurling and post-button accessibility before committing to a publish.
- Seamless integration with existing Openclaw Skills automation hooks for multi-agent content pipelines.
SKILL.md
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