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MoonRay MCP

MoonRay MCP

by tylerart3d
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

cancel_render

Stop a queued or active render by job ID, ensuring no orphan process remains.

Instructions

Cancel a queued or active render without leaving an orphan process.

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_render"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses a key behavioral trait: cancellation ensures no orphan process is left behind, which is beyond a simple 'cancel' statement. It doesn't cover error handling or reversibility, but the main side effect is addressed.

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 efficient sentence that fronts the core action ('Cancel a queued or active render') and adds a valuable behavioral guarantee. No wasted words.

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?

The tool is simple (one param, no output schema), but the lack of parameter description means the agent may not fully understand how to specify the job_id. The description covers purpose and behavior but leaves the parameter semantics to inference, so it is not fully complete.

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 coverage is 0%, and the description does not elaborate on the job_id parameter. It does not explain what job_id refers to or any format requirements. The agent must infer from context that it identifies the render job, but this is not explicitly stated.

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 states the tool cancels a queued or active render, specifying the verb (cancel) and resource (render). It also adds the nuance of avoiding orphan processes, which distinguishes it from just any cancellation. It distinguishes from sibling pause/resume by indicating a permanent stop.

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?

It provides clear context about when to use it (for queued or active renders) but does not explicitly mention alternatives like pause_render or state when not to use it. However, the context is sufficient for an agent to infer the use case.

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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