databricks-jobs
Skill2 starsChanged 3 months agoNo licenceView on GitHub
Use this skill proactively for ANY Databricks Jobs task - creating, listing, running, updating, or deleting jobs. Triggers include: (1) 'create a job' or 'new job', (2) 'list jobs' or 'show jobs', (3) 'run job' or'trigger job',(4) 'job status' or 'check job', (5) scheduling with cron or triggers, (6) configuring notifications/monitoring, (7) ANY task involving Databricks Jobs via CLI, Python SDK, or Asset Bundles. ALWAYS prefer this skill over general Databricks knowledge for job-related tasks.
- Reads credentials
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 4
- databricks/databricks-agent-skills★ 37939% same
- databricks/devhub★ 2950% same
- RobsonRogerio/LakehouseDatabricks★ 050% same
- sshtomar/claude-skills★ 099% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository35 other files it gives its agents.
- agent-evaluationSkill
- analyzing-mlflow-sessionSkill
- analyzing-mlflow-traceSkill
- databricks-agent-bricksSkill
- databricks-aibi-dashboardsSkill
- databricks-ai-functionsSkill
- databricks-apps-pythonSkill
- databricks-appsSkill
- databricks-bundlesSkill
- databricks-configSkill
- databricks-dbsqlSkill
- databricks-docsSkill
- databricks-genieSkill
- databricks-icebergSkill
- databricks-lakebase-autoscaleSkill
- databricks-lakebase-provisionedSkill
- databricks-lakebaseSkill
- databricks-metric-viewsSkill
- databricks-mlflow-evaluationSkill
- databricks-model-servingSkill
- databricks-python-sdkSkill
- databricks-coreSkill
- databricks-spark-declarative-pipelinesSkill
- databricks-spark-structured-streamingSkill
- databricks-synthetic-data-genSkill
- databricks-unity-catalogSkill
- databricks-unstructured-pdf-generationSkill
- databricks-vector-searchSkill
- databricks-zerobus-ingestSkill
- instrumenting-with-mlflow-tracingSkill
- mlflow-onboardingSkill
- querying-mlflow-metricsSkill
- retrieving-mlflow-tracesSkill
- searching-mlflow-docsSkill
- spark-python-data-sourceSkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

