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by 316sandon12
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Python
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inspect_library

List curated styles, quality budgets, recipe parameters, and semantic part names to guide Blender Python asset creation and Unity import.

Instructions

List curated styles, quality budgets, recipe parameters and semantic part names.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "inspect_library"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. 'List' implies a read-only, non-destructive operation, but the description says nothing about scope (global vs project), whether results are cached/stale, or how large the payload is. For a tool with zero annotation coverage this is thin.

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?

A single front-loaded sentence with no filler, and the enumeration is compact. It could arguably be tightened, but nothing is wasteful.

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?

With no output schema, no annotations, and no parameters, the description is the only source of information, and it only gives broad category names rather than the shape or fields of what is returned. It is minimally adequate but leaves the agent unable to predict the response structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters and the schema is empty, so there is nothing for the description to disambiguate. Baseline 4 applies; the enumeration of returned categories even adds slight value in the absence of an output schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a verb ('List') and enumerates the kinds of items returned (styles, quality budgets, recipe parameters, semantic part names), so the agent knows this exposes a catalog. However, it does not distinguish the tool from the many sibling inspection tools (inspect_target, inspect_scene, inspect_asset, inspect_performance), nor does it explain what 'the library' is. Purpose is inferable but vague.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to call this versus the other inspect_* siblings, and no mention of prerequisites or context. The agent must guess that this is a discovery/lookup step, likely before applying presets or styles.

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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