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ttiimmaacc

mcp-for-clo3d

by ttiimmaacc

get_fabric_info

Retrieve a fabric's name, content, classification, supplier, and CLO fabric info JSON by providing its fabric index.

Instructions

A fabric's name, its information fields (content, classification, supplier...) and CLO's fabric info JSON.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fabric_indexYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the data returned but does not state that it is a read-only operation (implied by 'get'), nor does it describe error behavior, required permissions, or side effects. The description is too terse to fully disclose behavior.

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 one concise sentence, front-loading the key details about the returned data. It avoids unnecessary words and is easy to read. It could be slightly clearer in structure but is appropriately sized.

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?

For a simple getter with one parameter and no output schema, the description offers a minimal specification: it lists the returned fields and mentions the JSON format. However, it lacks details on error handling, the exact JSON structure, and any prerequisites. It is minimally complete but not thorough.

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?

The input schema has only one parameter, fabric_index, with no description provided (schema coverage 0%). The tool description does not explain the parameter or how it relates to the returned data. The agent must rely on the parameter name alone, which is a gap given the zero coverage.

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 what the tool returns: a fabric's name, information fields, and CLO's fabric info JSON. It identifies a specific resource (a single fabric) and distinguishes from siblings like get_fabric_list (which lists fabrics) and set_fabric_information (which mutates). It is not a tautology, though it could be more explicit about retrieving data.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention alternative tools, prerequisites, or contexts. An agent would have to infer usage from the name and siblings, which is insufficient.

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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