linkedin

This LinkedIn integration skill empowers AI agents to seamlessly interact with professional networking data through the Membrane platform. By leveraging the Membrane CLI, users can manage their LinkedIn presence, including profile management, network connections, organization administration, and content engagement. The skill acts as an intelligent bridge, allowing agents to execute professional workflows such as publishing updates, monitoring social interactions, and retrieving organizational data without manual intervention. It is designed for professionals, recruiters, and social media managers who want to automate their LinkedIn activity while maintaining security and privacy through managed authentication.

• Full support for LinkedIn profile operations, including retrieval of experience, education, skills, and professional recommendations.

• Advanced post management capabilities: create text or image posts, delete posts, and manage reactions or comments.

• Organization and administrative tools: retrieve organization details, manage company pages, and access user-linked organization data.

• Automated authentication flow: handles credential refresh and token lifecycle management server-side via Membrane, eliminating the need to store local API keys or tokens.

• Dynamic action discovery: use natural language intents to search for, verify, and execute available LinkedIn actions.

• On-the-fly extensibility: if a specific action is missing, the skill supports automatic generation of new actions via Membrane's backend capabilities.

• Prerequisites include the installation of the Membrane CLI and a valid LinkedIn connection established through the membrane connect command.

• Ideal for headless agent environments; provides a JSON-based output format for machine-readable data processing.

• Follows best practices by preferring pre-built Membrane actions for pagination, error handling, and field mapping over raw API calls.

• Always use --json flag to receive structured data suitable for agent consumption and logic parsing.

• To discover capabilities, use membrane action list with natural language queries to identify the correct action ID before execution.

• If an action state returns BUILDING, use the membrane action get command with the --wait flag to poll for completion before running the task.