Scan an ML repository and generate a StartingPointReport for EVOR missions.
npx skills add https://github.com/it-dainb/oh-my-evor --skill evor-distill
Please help me install this Agent Skill. Skill: evor-distill Source: https://github.com/it-dainb/oh-my-evor/tree/main/skills/evor-distill Command: npx skills add https://github.com/it-dainb/oh-my-evor --skill evor-distill
This Skill helps automate the preparation of an ML workspace for the EVOR engine, by scanning and generating a StartingPointReport that aids in setting up EVOR missions.
Run /evor-distill /path/to/your/workspace to initiate the scan of your ML workspace.
High-intent search queries and answers about installing and using this skill.
To generate a starting point report for autonomous optimization, you can scan an ML repository to identify datasets, models, and configurations by running a simple command targeting your workspace path. This catalogs your ML artifacts and prepares the foundation for EVOR missions.
The best way to prepare an ML workspace for EVOR mission setup is to scan your existing repository to catalog checkpoints, configs, and entry points. This generates a StartingPointReport that provides insight into your ML artifacts and facilitates the setup process.
Yes, generating a workspace analysis report requires access to the specified ML workspace and a functional EVOR setup. The Skill relies on the EVOR engine environment to scan repositories and pre-fill the evor-setup interview effectively.
You can catalog datasets and checkpoints in an existing machine learning repository by running a workspace scan. The process identifies ML artifacts and configurations within your codebase, automatically generating a report that catalogs these components for optimization missions.
Yes, you can pre-fill the evor-setup interview using a repository scan. The generated StartingPointReport identifies your ML artifacts and configurations, integrating directly into the EVOR workflow to enhance and streamline the setup process.
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