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blender-lab-mcp-client

by A-to-PC

blender_job_cancel

Cancel a running or queued async Blender job by setting its cancel event, allowing scripts that check it to stop gracefully.

Instructions

Cancel a running or queued async Blender job. The job's cancel_event is set; scripts that check it will stop gracefully.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description must disclose behavior. It does disclose that the tool sets a cancel event and that scripts checking it will stop gracefully, which is valuable. However, it does not mention potential side effects, whether the operation is reversible, or error conditions (e.g., job not found). The disclosure is present but not comprehensive.

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 two concise sentences with no fluff. The primary action is front-loaded, and the second sentence adds a useful behavioral detail. Every word earns its place.

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?

The tool is simple with one parameter and an output schema exists, so the return format does not need to be described. The description covers the main behavior and the mechanism. Missing details like error handling for already-completed jobs are minor given the tool's simplicity and the presence of an output schema.

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%, so the description must compensate for the job_id parameter. The description only implies that job_id identifies the job to cancel; it does not explicitly explain the parameter's meaning, format, or how to obtain it (e.g., from blender_job_list). This leaves the parameter under-specified.

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 states a specific verb 'Cancel' and a specific resource 'a running or queued async Blender job', clearly distinguishing it from siblings like blender_job_list and blender_job_status. It also explains the mechanism (setting __cancel_event__), which is unambiguous.

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?

The description clearly indicates the tool is for cancelling async jobs, which gives context for when to use it. However, it does not explicitly mention when not to use it (e.g., if the job has already completed) or mention alternatives. It is clear enough for an agent to infer usage, but lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.