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larpingvibecoder

clo3d-mcp

fabric_library

Find available .zfab fabrics in CLO's asset library and apply an optional substring filter to narrow results.

Instructions

List .zfab fabrics available in the CLO asset library (optionally filtered by substring).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description implies a read-only operation (listing) but does not explicitly state that it has no side effects, nor does it describe the return format or any potential errors. For a simple list tool, this is acceptable but not exhaustive. The agent must infer that this operation is safe and non-mutating.

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, compact sentence that front-loads the core action and includes the optional parameter behavior. There is zero redundancy or filler. Every word contributes to understanding what the tool does.

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?

Given the tool's simplicity (one optional parameter, no output schema, no annotations), the description covers the essential aspects: what it lists, the scope, and the filter. It does not describe the output format or error conditions, but for a list operation, an agent can reasonably expect a list of fabric identifiers or paths. The absence of an output schema means the description doesn't need to explain return values, but it could have mentioned the structure of the list. Overall, it is sufficiently complete for correct invocation.

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 input schema has no description for the 'filter' parameter (coverage 0%), so the description must compensate. The description explicitly states 'optionally filtered by substring', which explains the parameter's purpose and behavior. This adds meaning beyond the schema, which only provides a title and default. It could specify case sensitivity or exact matching, but the substring semantics are clearly conveyed.

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

Purpose4/5

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

The description clearly states a specific verb ('List'), a specific resource ('.zfab fabrics'), and a clear scope ('in the CLO asset library'). It also mentions the optional filter. While it doesn't explicitly name a sibling like fabric_list, the 'asset library' qualifier differentiates it from scene-based fabric tools, making the purpose clear and distinguishable.

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?

The description implies usage context through the phrase 'asset library', but it does not explicitly state when to use this tool over alternatives like fabric_list, nor does it mention exclusions or prerequisites. An agent would need to infer that this is for library items, not scene items. There is no explicit 'when to use' or 'when not to use' guidance.

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