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data_submit_job

Destructive

Submit a data job with a free-text objective and optional JSON inputs, routed through the domain-agent dispatcher under your authenticated tenant and company scope.

Instructions

Run the data domain agent action submit_job.

Routes through the platform's domain-agent dispatcher under your JWT, tenant, and company scope.

Args: message: Free-text objective for the action. inputs: Optional JSON string of structured inputs for the action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsNo{}
messageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. Addedv0.1.1

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already indicate non-readonly and destructive behavior, so the bar is lower. The description adds routing and scope context but does not describe what submitting a job actually does, whether it is asynchronous, or what side effects may occur.

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 compact and free of fluff. It states the action, routing context, and parameter meanings in a clear, organized manner without 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?

Given the generic nature of a job-submission action, the description provides enough context: what it does, how it routes, and what the parameters mean. It does not describe return values, but an output schema is indicated, so that burden is partially shifted.

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?

Schema coverage is 0%, but the Args section adds basic semantics: message is a free-text objective and inputs is an optional JSON string of structured inputs. This is helpful but leaves the internal meaning and expected format of both parameters quite shallow.

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 specifies the action as running the data domain agent action `submit_job` and notes routing through the platform's dispatcher under JWT/tenant/company scope. This is a specific verb+resource and is distinguishable from generic invoke/dispatch tools.

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?

It explains that this tool runs a data domain agent action and describes the parameters, but it does not explicitly state when to prefer this tool over alternatives or when not to use it. Usage context is implied but not fully articulated.

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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