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list_categories

Read-onlyIdempotent

Lists available model categories for search_models, helping you choose the right category before searching AI image, video, or audio models.

Instructions

Free. List the available model categories for search_models.

Input Schema

NameRequiredDescriptionDefault

No arguments

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?

Annotations already declare readOnly, idempotent, non-destructive and openWorld, so the safety profile is covered. The description adds one genuinely non-schema piece of context, "Free" (no credit cost), which is valuable for planning multi-call workflows; however it says nothing about return shape or whether the list is exhaustive or paginated.

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?

Nine words, zero waste. The cost note and the resource statement are both front-loaded and no filler sentences dilute the definition.

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?

For a zero-param read-only lookup with annotations covering safety and idempotency, this is nearly complete. The only gap is the absence of any hint about the returned category values (count, format, or whether they map 1:1 to search_models filters), which matters slightly more given there is no output schema.

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, so the baseline of 4 applies. The description correctly signals a parameterless call by saying nothing about inputs, and the empty schema confirms it.

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?

Specific verb+resource ("List the available model categories") tied to the sibling that consumes them (search_models), so the agent can tell it apart from get_model or get_playbook. It stops short of defining what a category is relative to model records, but the core purpose is unmistakable.

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?

"for search_models" implies the discovery pattern: call this first to learn valid category values before searching. There is no explicit when-not guidance and no stated alternative, so the usage is implied rather than spelled out.

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