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ChrisChoTW

databricks-mcp

by ChrisChoTW

get_job_run

Retrieve detailed information about a specific Databricks job execution using its run ID to monitor progress and analyze results.

Instructions

Get run details

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
run_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The implementation of the get_job_run MCP tool, which fetches job run details from the workspace client.
    def get_job_run(ctx: Context, run_id: int) -> Dict[str, Any]:
        """Get run details"""
        w = get_workspace_client()
        return w.jobs.get_run(run_id=run_id).as_dict()
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Get run details' implies a read-only operation but doesn't specify permissions, rate limits, error conditions, or what the output contains. It fails to disclose any behavioral traits beyond the basic action, making it inadequate for a tool with no annotation support.

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

Conciseness5/5

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

The description is extremely concise with just three words, 'Get run details', which is front-loaded and wastes no space. However, this brevity comes at the cost of being under-specified, but as per the scoring rules, it earns a high score for conciseness alone.

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 1 parameter with no schema description, no annotations, and an output schema exists (which might cover return values), the description is incomplete. It doesn't explain the tool's purpose in context, parameter meaning, or usage relative to siblings, making it insufficient for effective agent use despite the output schema potentially helping.

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?

The input schema has 1 parameter with 0% description coverage, meaning the parameter 'run_id' is undocumented. The description adds no information about what 'run_id' is, its format, or where to obtain it, failing to compensate for the schema's lack of documentation and leaving the parameter's meaning unclear.

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

Purpose2/5

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

The description 'Get run details' is a tautology that essentially restates the tool name 'get_job_run' without adding meaningful specificity. It mentions the verb 'get' and resource 'run details' but doesn't clarify what a 'run' is in this context or what specific details are retrieved, making it vague rather than informative.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool versus alternatives like 'get_job', 'list_job_runs', or 'get_run_task_metrics'. The description provides no context, prerequisites, or exclusions, leaving the agent with no information to make an informed choice among sibling 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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