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Local Model MCP

Local Model MCP

by Doughboyfressh
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

cancel_job

Cancel a running model training or evaluation job cooperatively, then poll until it terminates; no partial model is published.

Instructions

Request cooperative cancellation. Poll until terminal; no partial model is published.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "job_id": "<job_id>"
    },
    "name": "cancel_job"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already establish that this is a non-read-only, non-destructive, closed-world operation. The description adds meaningful behavior beyond that: cancellation is cooperative rather than immediate, the caller must poll until a terminal state, and no partial model is published.

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?

Two short sentences, front-loaded with the action and followed by the key operational constraint. There is no wasted wording.

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. However, the description omits edge cases such as what happens if the job is already terminal, whether cancellation is idempotent, and how job_id should be supplied.

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 does not explain the sole job_id parameter, its format, or constraints. The schema pattern exists, but the description adds no meaning beyond the parameter name.

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 action, 'Request cooperative cancellation,' and the tool name identifies the resource as a job. It does not explicitly name a sibling alternative, but the cancellation purpose is clear enough to distinguish it from status or listing 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 gives post-call guidance ('Poll until terminal') but does not explicitly say when to use this tool versus job_status or list_jobs, nor when cancellation should be avoided. Usage is implied rather than fully specified.

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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