Explore databricks ai runtime as a ai & machine learning workflow from databricks/databricks-agent-skills. Compare its source, maintenance and review signals before choosing it for your agent.
This source provides a task-specific instruction workflow for AI & machine learning. Its source file is linked below so you can inspect the exact procedure, tools and dependencies. A full editorial review has not been completed.
Exploring AI & machine learning workflows with an agent. Confirm that the source matches your task and environment.
The automated catalog record does not establish task performance or runtime safety. Check supporting scripts and external services in the source before use.
Requires the Databricks CLI with the air command. Flattened code_source requires CLI 1.20.0 or newer; older CLIs can use the nested snapshot format documented below. See the [installation guide](https://docs.databricks.com/dev-tools/cli/install).
Inspect the pinned source snapshot and its supporting files first. The command selects this skill through the open-source skills CLI. Node.js and agent-specific setup may be required. Installation can download code; this catalog never runs it.
npx skills add https://github.com/databricks/databricks-agent-skills/tree/d50672205671c6d6edc847b1ddc36e7cba69bd32/skills/databricks-ai-runtime --skill databricks-ai-runtimeReview pinned skill folder ↗ · CLI documentation ↗
After source review, use npx skills check and npx skills update to inspect and apply upstream updates. Re-check changed instructions before running them.
Static review only. This is not a security audit or a guarantee of safety.
SKILL.md text only; scripts, dependencies and runtime behavior not audited.
Allowed tools declaration: Unknown. Runtime permissions and network behavior: Unknown.
74/100 · Metadata coverage 80% · Model 1.0
Scores summarize observable discovery signals. Popularity and repository activity apply to the whole repository. Unknown runtime safety earns no certification.
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A data-app design guide that maps analytical interfaces to concrete Databricks AppKit components.