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jobs_run_now

Trigger an immediate run of a Databricks job by specifying the job ID and optional parameters, and obtain the run ID for monitoring.

Instructions

Trigger a job run and return the run_id. By default, parameters not listed are taken from the job's existing parameter defaults.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesJob ID to run
notebook_paramsNo
python_paramsNo
jar_paramsNo
spark_submit_paramsNo
sql_paramsNo
dbt_commandsNo
idempotency_tokenNo
pipeline_paramsNo
queueNo
webhook_notificationsNo
timeout_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate a mutation (readOnlyHint=false), and the description correctly implies a write operation. However, it lacks disclosure of potential side effects, permissions required, or rate limits, which would add value beyond the annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short (two sentences) and front-loaded with the main action. However, it omits important parameter details that could be included without bloat, making it somewhat under-specified.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 12 parameters and an output schema, the description is incomplete. It explains the return of run_id but does not describe output structure or other possible return fields. Parameter usage is only vaguely addressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With only 8% schema description coverage, the description fails to clarify the meaning of the 11 undocumented parameters (e.g., notebook_params, python_params). The generic statement about defaults does not compensate for the lack of individual parameter explanations.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Trigger a job run') and the result ('return the run_id'). It distinguishes from sibling tools by specifying it initiates a run, as opposed to other operations like cancel or get.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions that unlisted parameters inherit job defaults, which guides usage for overrides. However, it does not provide explicit when-to-use or when-not-to-use guidance compared to other run-related tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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