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List models

models_list
Read-onlyIdempotent

Fetch every active model with capabilities, context window, and ruble price by paging through the full catalogue ordered by model ID. Use for caching, counting, or scanning when no filter applies.

Instructions

Walk the whole Hubris catalogue page by page, ordered by model id. Returns every active model with its capabilities, context window and ruble price.

Use this when you need the complete catalogue — to cache it, to count models, or to scan for something no filter covers. When you are looking for a model that fits a task, use models_search instead: it filters by capability, price and context server-side and saves you a few hundred rows.

Paging: read nextCursor from the response and pass it back as cursor. When nextCursor is absent you have reached the end. The catalogue holds roughly 550 models, so a full walk is about 11 calls at the default page size.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoModels per page, 1–200. Defaults to 50.
cursorNoThe `nextCursor` value from the previous response. Omit for the first page.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsYes
nextCursorNoPass back as `cursor` to fetch the next page. Absent when the last page was returned.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

The description goes beyond the annotations by explaining the pagination mechanism: 'Paging: read `nextCursor` from the response and pass it back as `cursor`. When `nextCursor` is absent you have reached the end.' It also provides an estimate of the number of calls needed ('about 11 calls at the default page size'), giving the agent a realistic expectation of the tool's behavior. The annotations already indicate read-only, idempotent, and non-destructive behavior, so no contradiction exists.

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 well-structured and concise. It starts with the core purpose, then explains when to use it, and finally details the pagination behavior. Each sentence serves a purpose, and there is no redundant or filler content. The structure is logical and easy to follow.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description does not need to list return fields, but it still mentions the key output attributes (capabilities, context window, price). It covers the pagination behavior, usage context, and the tool's scope. This is sufficient for an agent to understand what the tool does, when to use it, and how it behaves without needing to inspect additional references.

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

Parameters3/5

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

The schema descriptions fully cover both parameters (limit and cursor), including the default limit and the instruction to omit cursor for the first page. The description adds no additional semantic information about the parameters themselves; it only references the default page size in the context of the number of calls. Since the schema coverage is 100%, the baseline is 3, and the description provides no extra value beyond that.

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 tool's purpose: to walk the entire catalogue page by page, ordered by model id, returning every active model with its capabilities, context window, and price. It also distinguishes itself from sibling tools like models_search (which filters) and models_get_pricing (which gets specific pricing), so an agent can easily differentiate when to use this tool.

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

Usage Guidelines5/5

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

The description explicitly tells when to use this tool: 'Use this when you need the complete catalogue — to cache it, to count models, or to scan for something no filter covers.' It also provides an alternative: 'When you are looking for a model that fits a task, use models_search instead.' This gives clear, actionable guidance on both when to use and when not to use the tool.

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