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jaguarkyng

Jungle Grid MCP Server

by jaguarkyng

estimate_job

Read-only

Plan AI workloads by estimating routing, capacity source, and expected cost before submission, enabling informed decisions.

Instructions

Estimate routing, capacity source, and expected cost for a proposed Jungle Grid workload without submitting it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argsNo
imageNo
notesNo
commandNo
templateNo
model_sizeNoOptional model size in GB.
routing_modeNo
workload_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes

Schema Changelog

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

  1. First observedv0.20.2

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is established. The description adds meaningful behavioral context by explicitly stating that the workload is not submitted, which reinforces the non-mutating nature and clarifies that this is a dry-run style estimation.

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 a single, tight sentence that leads with the action verb and immediately states the tool's scope and non-effect. Every word contributes meaning; there is no filler or redundancy.

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

Completeness2/5

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

The tool has eight parameters, one required, and a very low schema description coverage; the description gives no guidance on what fields matter or how they interact. While an output schema exists, the description still leaves the agent under-equipped to construct a correct estimate request.

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

Parameters1/5

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

Schema description coverage is only 13%, with seven of eight parameters undocumented. The description does not explain any parameter names, relationships, or how to construct a valid workload estimate, so it fails to compensate for the sparse schema.

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 names a specific verb ('Estimate') with precise objects: routing, capacity source, and expected cost. The phrase 'without submitting it' clearly distinguishes this from submit_job, so an agent can tell them apart without inspecting schemas.

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?

The description implies the tool is for pre-submission planning ('for a proposed workload', 'without submitting it'), but it does not explicitly state when to choose this over alternatives such as submit_job or list_jobs. No exclusions are provided, and no sibling tool is named as the right choice when submission is actually desired.

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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