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List AI Studio models

list_studio_models
Read-onlyIdempotent

List the AI Studio image/video generation models available to this account: key, vendor, kind, modes (t2i, i2i, t2v, i2v…), configurable params with allowed values and defaults, required inputs, the starting credit price and whether the plan unlocks it. Use the key as model_key in studio_generate. Free.

Input Schema

NameRequiredDescriptionDefault
kindNoOnly this kind of model.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds a genuinely useful behavioral fact not in annotations — 'Free' (no credit cost) — plus a detailed account of what the response contains, which matters since there is no output schema.

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?

A single dense but front-loaded sentence: the action and scope come first, followed by the returned fields, the integration hint, and the cost note. Every clause earns its place, though the field enumeration makes it heavier than strictly necessary.

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?

With no output schema, the description compensates fully by enumerating the return payload (key, vendor, kind, modes, params with defaults, required inputs, credit price, plan unlock) and by naming the downstream tool that consumes the key. An agent has everything needed to call and use the result.

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?

Schema description coverage is 100% for the single optional 'kind' enum filter, so the schema carries parameter meaning. The description uses 'kind' only as a returned field, not to explain the filter parameter, so it adds nothing beyond the schema — baseline 3 applies.

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?

States a specific verb ('List') plus the exact resource ('AI Studio image/video generation models available to this account') and enumerates the returned fields, so it is clearly distinguishable from sibling list tools like list_studio_presets or list_voices. An agent knows precisely what this returns without opening the schema.

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

Usage Guidelines4/5

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

Explicitly routes the agent forward: 'Use the key as model_key in studio_generate,' which is the primary consumer of this tool. It also notes the tool is free, implying no credit cost, but gives no when-not-to-use guidance or prerequisites.

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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