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Get Job Result

get_job_result

Get the completed result of a background command, returning exit code, stdout, stderr, and duration. Waits for running jobs to finish up to their timeout.

Instructions

Fetch the completed result of a background command.

RETURNS the same shape as execute_experiment: exit code, stdout, stderr, duration. If the job is still running this waits for it, bounded by the job's own timeout.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesJob id to fetch.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
job_idYes
statusYes
stderrNo
stdoutNo
commandYes
exit_codeNo
duration_msNo
experiment_idYes
stderr_truncatedNo
stdout_truncatedNo

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It discloses the return shape (exit code, stdout, stderr, duration) and a key blocking behavior (waits for running jobs bounded by the job's timeout). It does not cover timeout failures or cancellation scenarios, but the disclosed traits are valuable.

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?

Two concise, front-loaded sentences: the first states the tool's purpose, the second supplies essential return and blocking behavior. No filler or redundant content.

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 tool with an output schema, the description covers the essential context: what it returns, when it blocks, and how it relates to execute_experiment. It could explicitly mention that job_id comes from execute_experiment, but this is a minor gap.

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?

The input schema fully describes job_id with 100% coverage. The description adds no extra parameter-level detail beyond the schema, so the baseline score of 3 applies.

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

Purpose4/5

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

States a specific verb ('Fetch') and resource ('completed result of a background command'). It implicitly distinguishes from get_job_status by focusing on result delivery rather than status, though it does not explicitly name the sibling alternative.

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?

Provides clear context: the tool retrieves results of a background command and waits if the job is still running. However, it does not explicitly state when to prefer get_job_status or cancel_job, so no direct exclusion or alternative guidance is given.

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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