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Glama

get_job_status

Read the persistent status and result of a long-running production job by project root and job ID, enabling progress tracking, output retrieval, and resumable workflow control.

Instructions

Read the persistent status and result of a long production job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes
project_rootYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It does disclose two useful traits — that the status is persistent (retrievable after the fact) and that the result is included — and 'Read' implies a non-mutating operation. It says nothing about behavior for an unknown job_id, polling frequency, or whether status can be stale/eventually consistent.

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?

A single front-loaded sentence with no filler, and the purpose is stated immediately. It is efficient, though the brevity comes partly at the cost of the missing parameter and usage detail rather than being purely economical.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and the tool is a simple two-parameter read. However, with no annotations and 0% parameter coverage, the definition leaves project_root's role and the relationship to cancel_job/resume_job entirely to inference.

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

Parameters2/5

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

Schema description coverage is 0% and the description compensates for almost none of it. The word 'job' weakly implies job_id, but project_root — a required parameter — is never mentioned, so the agent gets no guidance on what it is or how it scopes the lookup.

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?

The description states a specific verb (Read) and resource (persistent status and result of a long production job), which is clearly distinct from the mutation siblings cancel_job and resume_job. It never names those siblings or explicitly contrasts itself with them, so it stops short of full sibling differentiation.

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

Usage Guidelines3/5

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

Usage is only implied: an agent can infer this is the tool to poll after kicking off a long job. There is no explicit when-to-use, no statement of prerequisites, and no reference to the adjacent cancel_job/resume_job tools that operate on the same job_id.

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