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upscale-mcp

upscale-mcp

by sidney
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

jobs_cancel

Cancel a queued image-upscaling job or stop a running one at the next tile boundary. Cancelled jobs write no output; check job status if a running job still reports as running.

Instructions

Cancel a queued job, or stop a running one after the tile it is working on.

A running job stops at the next tile boundary, so the returned status may
still be "running"; check job_status. A cancelled job writes no output.

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": "<job>"
    },
    "name": "jobs_cancel"
  }
}

Input Schema

NameRequiredDescriptionDefault
jobYesJob id to cancel.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and discloses key behaviors: a running job stops at the next tile boundary, the returned status may still be 'running', and a cancelled job writes no output. It does not cover permissions or error cases, but the core cancellation semantics are well explained.

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?

Three short sentences with no waste. The core action is front-loaded, followed by the tile-boundary behavior and the output consequence. Every sentence earns its place.

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

Completeness5/5

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

For a one-parameter mutation tool with no output schema or annotations, the description is complete enough. It explains the cancellation effect, the status caveat, and the lack of output, so an agent has what it needs to invoke and interpret the call.

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 description coverage is 100%, and the schema already defines the single 'job' parameter as 'Job id to cancel.' The description adds no additional parameter syntax or format details, so the baseline of 3 is appropriate.

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: 'Cancel a queued job, or stop a running one.' It also clarifies the queued vs running distinction and references the job_status sibling for follow-up, so an agent can distinguish it from status/list tools.

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?

Provides clear context for use: cancel a queued job or stop a running one, and check job_status afterward. It does not name explicit exclusions or alternatives, but no sibling offers cancellation, so the context is sufficient.

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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