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StockCake

List StockCake AI Models

list_models
Read-onlyIdempotent

Image and video models available to generate_image / create_video with the credit price of every tier. Free-credit models are flagged; video is priced per second. Requires a free StockCake account (the host will prompt to sign in).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoReturn only one catalog
contextYesIn one sentence, what is the user trying to make or find?
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
conversation_idNoPass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so safety is covered. The description adds genuinely new behavioral context: an auth requirement (free StockCake account, host prompts sign-in) and pricing semantics (video billed per second, free-credit models flagged).

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?

Two dense sentences, front-loaded with what the tool returns and followed by pricing and auth caveats. No filler, nothing restated from the title.

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?

With an output schema present, return-value documentation is unnecessary, and the description covers the auth prerequisite and pricing model. It could have been slightly more explicit about when to call it relative to the generation tools, but nothing needed to invoke it correctly is missing.

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%, so the parameters are fully documented in the schema and the baseline is 3. The description corroborates that the result is split into image and video catalogs and explains pricing units, but adds no syntax or usage detail beyond what the schema already supplies.

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 states exactly what is returned: image and video models with per-tier credit prices, free-credit flags, and per-second video pricing, and ties the catalog to the sibling tools that consume it (generate_image / create_video). It is clear which resource is being enumerated, though the listing verb itself is only implied by the name/title.

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?

The description implies the catalog is consulted before calling generate_image or create_video, and the kind parameter narrows it to one catalog, but there is no explicit 'call this when…' guidance or statement of when to skip it. Usage is inferable rather than stated.

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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