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blender_status

Check Blender availability, system resources, and performance metrics through configurable monitoring operations.

Instructions

System status and monitoring (portmanteau).

Operations:

  • status: MCP server, Blender, system, and performance summary

  • system_info: Detailed OS, Python, env, and resources

  • health_check: Blender availability, resources, tool registration

  • performance_monitor: Sample CPU/memory/disk over duration_seconds (max 60)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operationNostatus | system_info | health_check | performance_monitorstatus
include_blender_infoNoFor status — include Blender section
include_system_infoNoFor status — include system section
include_performanceNoFor status — include performance section
duration_secondsNoFor performance_monitor — sampling duration (1-60)
limitNo
formatNo"json" for webapp dict (status only); "text" for report stringtext

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It does not mention that the tool is read-only, what authentication is needed, or any side effects. The operations are listed but not described in terms of impact, leaving the agent uncertain about safety.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a brief introductory sentence and a bullet list of operations. It is concise and front-loaded, though the term 'portmanteau' is unnecessary and could confuse.

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, with 7 parameters and no usage examples, the description is adequate but not rich. Missing details like rate limits or performance implications for the monitoring operations.

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 high (86%), so the baseline is 3. The description adds little beyond the schema, merely repeating operation options without additional context like format examples or default behaviors.

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 uses specific verbs ('status', 'system_info', 'health_check', 'performance_monitor') and clearly identifies the resource as system status and monitoring. It distinguishes from sibling tools by focusing on non-Blender operational monitoring, which is unique among the sibling list.

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?

While the description lists operations and parameters, it provides no explicit guidance on when to use this tool versus alternatives. Given the large number of sibling tools, the lack of contextual usage advice limits clarity.

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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