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Get Job Status

get_job_status

Check the status and details of a running or completed job in Microsoft Fabric, including NotStarted, InProgress, Completed, Failed, or Cancelled states.

Instructions

Get status of a specific job instance.

Retrieves the current status and details of a running or completed job. The job state includes: NotStarted, InProgress, Completed, Failed, Cancelled.

Parameters: workspace_name: The display name of the workspace. item_name: Name of the item. item_type: Type of the item (Notebook, Pipeline, etc.). job_instance_id: ID of the job instance to check.

Returns: Dictionary with status, message, and job details including: - job_instance_id, item_id, job_type, job_status - invoke_type, root_activity_id, start_time_utc, end_time_utc - failure_reason (if failed) - is_terminal, is_successful, is_failed, is_running flags

Example: ```python result = get_job_status( workspace_name="My Workspace", item_name="analysis_notebook", item_type="Notebook", job_instance_id="12345678-1234-1234-1234-123456789abc" )

if result["job"]["is_terminal"]:
    if result["job"]["is_successful"]:
        print("Job completed successfully!")
    else:
        print(f"Job failed: {result['job']['failure_reason']}")
```

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspace_nameYes
item_nameYes
item_typeYes
job_instance_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it retrieves current status and details, lists possible job states, and describes the return structure including flags like 'is_terminal'. It does not mention rate limits, authentication needs, or error handling, leaving some gaps.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded with the core purpose, followed by details and an example. Some sentences could be more concise (e.g., the parameter list is verbose), but overall it's well-structured with no wasted content.

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

Completeness5/5

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

Given the tool's moderate complexity, no annotations, 0% schema coverage, but with an output schema (implied by 'Returns' section), the description is complete. It covers purpose, parameters, return values, and includes an example, providing all necessary context for an agent to use the tool effectively.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate fully. It does so by listing all 4 parameters with clear explanations (e.g., 'ID of the job instance to check') and providing an example that demonstrates usage. This adds significant meaning beyond the bare schema.

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 tool's purpose with specific verb ('Get status') and resource ('job instance'), and distinguishes it from siblings like 'get_job_status_by_url' by specifying it retrieves status for a specific job instance. The title and name align perfectly with the described functionality.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool ('to check' a job instance), but does not explicitly mention when not to use it or name alternatives like 'get_job_status_by_url' from the sibling list. The example implies usage for monitoring job completion, which is helpful but not exhaustive.

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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