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Glama

diana_job_status

Read-only

Retrieve status, progress, and errors for background DIANA solver jobs, or list up to 20 recent jobs when no job ID is provided.

Instructions

Status of a background solver job, or of the 20 most recent jobs when no id is given.

Includes state (running/finished/failed/cancelled), elapsed time, output file sizes and the progress read from the .out file: analysis blocks, load steps, convergence and errors.

Args: job_id: id returned by diana_solve or diana_run_solver. tail_lines: also return the last lines of the .out file.

Input Schema

NameRequiredDescriptionDefault
job_idNo
tail_linesNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.10.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations only declare readOnlyHint and openWorldHint, so the description carries the substance: it enumerates the job states reported (running/finished/failed/cancelled), the elapsed time and output file sizes, and that progress is parsed from the .out file (analysis blocks, load steps, convergence, errors). It does not state answer for jobs that no longer exist on disk or what happens if job_id is unknown.

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 core behaviour and the no-id default are front-loaded in the first sentence, then the returned content, then per-argument notes. The Args block mostly restates the schema titles but earns its place by adding the job-id provenance and the tail behaviour.

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?

It is a read-only, two-parameter tool with an output schema, so return-shape documentation is optional yet present. The only noticeable gaps are the integer semantics of tail_lines and behaviour for stale or unknown job ids, which are minor for this complexity level.

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

Parameters4/5

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

Schema coverage is 0%, so the description must document both parameters. It does: job_id is 'id returned by diana_solve or diana_run_solver', and tail_lines 'also return[s] the last lines of the .out file'. The tail_lines wording reads more like a boolean than an integer count, leaving the value semantics slightly ambiguous.

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 ('Status of a background solver job') plus the default behaviour with no id (20 most recent jobs). The word 'solver job' plus references to diana_solve/diana_run_solver clearly separate it from the other *_status siblings (diana_status, diana_review_status, diana_community_status).

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 makes the selection condition clear: pass an id for one job, omit it to list the 20 most recent, and it names diana_solve and diana_run_solver as the sources of those ids. It does not mention alternatives such as diana_read_out for reading .out content or diana_job_cancel, so there are no explicit when-not rules.

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