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Get Job Status

get_job_status

Check a background command's status by job ID, including elapsed milliseconds. Poll until status shows finished, then retrieve the result.

Instructions

Check on a command started with background=true.

RETURNS status and elapsed milliseconds. Poll this, then call get_job_result once finished is true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesJob id from execute_experiment.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes
statusYes
commandYes
finishedNo
exit_codeNo
elapsed_msYes
experiment_idYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses read-only polling semantics, the elapsed-milliseconds return, and a terminal condition (`finished`). However, it does not specify the status vocabulary or failure-mode behavior — e.g., whether a failed or cancelled job ever reaches `finished`, which is a clear gap for an agent polling a background job.

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?

Three sentences, no filler: purpose first, then return values, then the polling next-step. Every sentence earns its place and the key behavioral instruction is front-loaded.

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

Completeness4/5

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

For a one-parameter, read-only polling tool with an output schema present, the description covers the core workflow completely: what it checks, what it returns, and what to do when done. The only meaningful omission is guidance for terminal states other than `finished` (failure/cancellation), but the output schema likely documents status values.

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

Parameters3/5

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

Schema coverage is 100% and job_id is already documented as 'Job id from execute_experiment.' The description adds contextual value by tying job_id to commands started with background=true, but it doesn't add parameter-specific syntax or format details beyond the schema, so the baseline of 3 is appropriate.

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?

States a specific verb and resource: 'Check on a command started with background=true.' It also says what it returns (status, elapsed milliseconds), and the polling-then-result flow clearly distinguishes it from get_job_result, which retrieves the job's output rather than its status. The scope is precise and disambiguating.

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

Usage Guidelines5/5

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

Gives explicit usage flow: poll this for background commands, wait until `finished` is true, then switch to get_job_result. It names the sibling tool and the exact condition for switching, which is exactly the routing guidance an agent needs.

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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