Explain recent job failures
Summarize execution states and useful error details for a selected job.
/oo Databricks: Review job [job ID] during [time range]. Inspect failed runs and summarize affected tasks, errors, and follow-up checks.
Find the failed task and the evidence needed for the next investigation step.
Copy a prompt into your agent with the oo Skill installed. Add your page links and source notes before running it.
Summarize execution states and useful error details for a selected job.
/oo Databricks: Review job [job ID] during [time range]. Inspect failed runs and summarize affected tasks, errors, and follow-up checks.
Run the chosen workload with the supplied parameters and report its run identifier.
/oo Databricks: Start existing job [job ID] with [parameters] for [purpose]. Check its current progress and tell me whether it has finished.
Set up oo CLI and the oo Skill in your agent.
Install OOMOL →Connect with a Databricks personal access token and workspace URL.
Connect Databricks →Use /oo with the pages to read, the changes to make, and where to save the result.
Connection Guide →Choose Your Agent
Inspect job definitions, run states, and available output, or start an existing workload with supplied parameters.
Read workload definitions, execution states and run output.
Start a job with its identifier and optional workload parameters.
Get the current Databricks workspace principal profile for the connected personal access token.
databricks.get_current_user List Databricks jobs in the connected workspace with optional pagination, name filtering, and task expansion.
databricks.list_jobs Get one Databricks job, including its current settings and optional continuation page token.
databricks.get_job Create a Databricks job from a raw official Jobs API settings object and return the new job ID.
databricks.create_job Update an existing Databricks job by ID using the official partial-update payload fields.
databricks.update_job_by_id Delete a Databricks job by ID.
databricks.delete_job Trigger an immediate run for a Databricks job with optional parameter maps and idempotency token.
databricks.run_now_job List Databricks job runs with optional job, state, time-range, and pagination filters.
databricks.list_runs Get one Databricks job run by run ID.
databricks.get_run_by_id Get the output payload for one Databricks run, including notebook output or error details when available.
databricks.get_run_output Cancel a Databricks job run by run ID.
databricks.cancel_run Submit a one-time Databricks run from a raw official Jobs API submit payload and return the run ID.
databricks.submit_run List Databricks clusters with optional paging, filtering, and sorting controls from the official clusters API.
databricks.list_clusters Get one Databricks cluster by cluster ID.
databricks.get_cluster Create a Databricks cluster from a raw official clusters create payload and return the new cluster ID.
databricks.create_cluster Edit an existing Databricks cluster by cluster ID using a raw official clusters edit payload.
databricks.edit_cluster Start a terminated Databricks cluster by cluster ID.
databricks.start_cluster Permanently delete a Databricks cluster by cluster ID.
databricks.permanent_delete_cluster List Databricks cluster node types that are available in the connected workspace region.
databricks.list_cluster_node_types List Databricks cluster availability zones for the connected workspace when the API is supported.
databricks.list_cluster_zones List Databricks Runtime and Spark versions that can be used when creating or editing clusters.
databricks.list_cluster_spark_versions List the direct Databricks workspace objects under a workspace path.
databricks.workspace_list Get metadata for one Databricks workspace object by absolute path.
databricks.workspace_get_status Export one Databricks workspace object as base64 content or direct text content, depending on the export mode.
databricks.workspace_export Import base64 content into the Databricks workspace at an absolute path.
databricks.workspace_import Create a Databricks workspace directory, including any missing parent directories.
databricks.workspace_mkdirs Delete a Databricks workspace object or directory by absolute path.
databricks.workspace_delete Create a Databricks workspace repo that links a Git remote into the connected workspace.
databricks.create_repo Update a Databricks workspace repo by switching branch or tag, or by changing sparse-checkout settings.
databricks.update_repo Delete a Databricks workspace repo by repo ID.
databricks.delete_repo List Databricks secret scopes in the connected workspace.
databricks.list_secret_scopes List Databricks secret metadata rows in one secret scope.
databricks.list_secrets Create a Databricks secret scope with an optional backend configuration and initial manager principal.
databricks.create_secret_scope Delete a Databricks secret scope by scope name.
databricks.delete_secret_scope Create or overwrite a Databricks secret value inside one Databricks secret scope.
databricks.put_secret Delete one Databricks secret value from a Databricks secret scope.
databricks.delete_secret No matching tools.
Yes. It executes the selected workload and may incur compute costs.
The available operations cover jobs, runs, and workspace resources. They do not include direct SQL warehouse queries.
Manage which optional storage OOMOL can use. You can change these choices from the footer at any time.