3dassets

Find AI models

list_ai_models

Search OpenRouter for model suggestions, updated hourly. Accept custom names; missing suggestions don't block uploads.

Instructions

Search model suggestions from OpenRouter, refreshed hourly. Custom model/tool names are accepted; the list is not exhaustive. Unavailable suggestions never block uploads.

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": "list_ai_models"
  }
}

Input Schema

Name	Required	Description	Default
`q`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 8, 2026

TDQS

B3.2/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses freshness ('refreshed hourly'), completeness ('not exhaustive'), and non-blocking behavior ('never block uploads'), which is helpful, but it omits details on permissions, rate limits, errors, or side effects. This is partial transparency.

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 three sentences, each carrying meaningful information without redundancy. It is tightly written and front-loads the primary action before adding secondary details.

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?

Given the tool's simplicity and the absence of an output schema, the description covers core aspects like source, refresh policy, and non-blocking behavior. However, it does not describe the shape or content of the returned model suggestions, which would be helpful for an agent to understand the tool's full utility.

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

Parameters1/5

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

There is only one parameter (q), and the description provides no explanation of what q means or how it is used. The schema itself also lacks a description for q, so there is zero coverage. The description fails to compensate, leaving the parameter completely unexplained.

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 clearly states the action ('Search'), the resource ('model suggestions'), and the source ('OpenRouter'). It distinguishes this tool from other listing/search tools by focusing on models specifically.

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 some usage context (e.g., 'refreshed hourly', 'not exhaustive', 'unavailable suggestions never block uploads') but does not explicitly state when to use this tool versus any alternative, and no sibling tools are mentioned. Guidance remains implicit rather than explicit.

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