Generate lab YAML, logo, and initial outputs for the Labs tracker.
npx skills add https://github.com/hammer/labs --skill add-lab
Please help me install this Agent Skill. Skill: add-lab Source: https://github.com/hammer/labs/tree/main/.agents/skills/add-lab Command: npx skills add https://github.com/hammer/labs --skill add-lab
Onboarding a new AI lab into the Lab Tracker is often manual, error-prone work that requires creating and updating multiple files, assets, and references. This Skill automates the generation of a consistent lab entry, logo scaffolding, and initial outputs, reducing setup time and keeping data synchronized.
Run the add-lab workflow with the lab’s basic details to generate the YAML, logo, and output scaffolds.
High-intent search queries and answers about installing and using this skill.
Automating AI research lab onboarding requires generating a standardized lab YAML file, logo scaffolding, and initial outputs. This ensures consistent population of fields like name, slug, region, and founding year while validating required assets.
Generating a lab YAML entry requires populating fields like name, slug, url, region, founded, type, description, people, news, and outputs. Validation checks ensure logo presence and correct OpenRouter links when available.
Yes, automation can scaffold initial outputs for flagship AI models, papers, or datasets based on the lab's focus. This creates structured entries within the lab YAML, ensuring research outputs are consistently tracked.
Yes, lab onboarding automation validates logo presence and checks OpenRouter links when available. It ensures required YAML fields are correctly formatted and notes legacy organizations and regional classifications.
The best way to keep lab tracker data synchronized is automating the creation of the lab YAML, logo assets, and initial outputs simultaneously. This reduces manual setup errors and pushes updates to the README and region index.
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