Skip to main content
Glama

Get Job Status

get_job_status

Check the status of a background command by job ID, returning current state and elapsed milliseconds to determine when it finishes.

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?

No annotations are present, so the description carries the full burden. It implies a non-mutating status check and mentions returned values, but it does not explicitly state side effects, idempotency, or authorization requirements.

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 two short sentences that communicate purpose, output, and the follow-up action without unnecessary detail.

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 simple polling status tool, the description is nearly complete: it defines what is returned, the completion condition, and the next step. It lacks an explicit output schema or status value enumeration, but these are not critical given the simple use case.

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 single param job_id is described in the schema as 'Job id from execute_experiment,' which is clear. The tool description adds no further parameter detail, but schema coverage is complete for the only input.

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: checking on a background command started with background=true, and it explicitly distinguishes its output (status and elapsed milliseconds) from the later retrieval step (get_job_result).

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?

The description gives direct usage guidance: poll this tool until 'finished' is true, then call get_job_result. This explicitly names the companion tool and the correct sequencing, leaving little ambiguity.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/riyasaxena32/sandbox-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server