Automate LinkedIn Commander onboarding with interviews, post analysis, and data seeding.
npx skills add https://github.com/sabania/linkedin-cli --skill setup-sabania
Please help me install this Agent Skill. Skill: setup Source: https://github.com/sabania/linkedin-cli/tree/main/plugin/skills/setup Command: npx skills add https://github.com/sabania/linkedin-cli --skill setup-sabania
This Skill automates the comprehensive setup and initial data seeding for the LinkedIn Commander, ensuring the system starts with real-world context and is immediately operational.
config.json, CLAUDE.md) and populates data storage (e.g., Excel sheets) with initial findings./setup. The Skill guides them through defining their business objectives, target audience, and content preferences, then analyzes their last 30 posts to understand what resonates, populating the system so the first /auto command provides meaningful insights.Run the setup skill to begin the deep onboarding process for LinkedIn Commander.
High-intent search queries and answers about installing and using this skill.
LinkedIn onboarding is automated by conducting conversational interviews to define goals and ICP, analyzing historical post performance, and seeding the CRM contact database. This generates configuration files so the system starts warm with actionable data.
Establishing a LinkedIn performance baseline is done by analyzing your past posts to identify content patterns and scoring high-value engagers. This historical data analysis populates Excel data stores to provide immediate, meaningful insights.
Yes, openpyxl is required to generate and populate Excel data stores for CRM contact seeding. This dependency allows the setup process to create configuration files and save initial findings regarding high-value engagers.
Yes, you can define your Ideal Customer Profile and content strategy conversationally through a guided interview. The setup process collects your business objectives, target audience, and competitor information to configure the system automatically.
A cold CRM database lacks baseline performance data and scored contacts, limiting automated LinkedIn outreach. Seeding the database with high-value engagers ensures the first automated commands yield meaningful insights.
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