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List available models

list_models
Read-onlyIdempotent

Lists available image/video models, grouped by role, with output type, estimated credit cost, price tier, mode/latency, and a one-line description. Each "model" value passes to generate_image or generate_video. Filter by role or output_type, or sort "cost" for cheapest first. Video estimates assume a 5s clip; pass estimate_only to generate_image/generate_video for an exact quote. Each entry also has speed_tier (fast, balanced or quality), credits, typical_seconds when known, and best_for. Use these to offer a faster or higher-detail option.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roleNoOptional job filter. Omit to list every model.
sortNoOptional: "cost" sorts cheapest (by estimated credits) first. Default keeps the role grouping.
output_typeNoOptional filter: image or video.

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 establish readOnly/idempotent/non-destructive/closed-world, so the lower bar applies. The description still adds non-obvious behavior: video cost estimates assume a 5s clip, and the listed credits are estimates only unless an exact quote is requested. That caveat materially affects how an agent should present costs.

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?

Roughly five front-loaded sentences with no filler, leading with what is listed and closing with how to act on the fields. Slight redundancy in listing cost/credits fields twice ('estimated credit cost' then 'credits') keeps it just short of 5.

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 carries the burden of describing return fields and does so thoroughly (grouping, type, cost, tier, latency, speed_tier, typical_seconds, best_for), plus the estimation caveat. An agent has everything needed to call it 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% with all three parameters enum-documented, so the baseline is 3. The description reinforces the filters and clarifies that sort 'cost' orders by estimated credits, but adds little beyond the schema text itself.

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 and resource ('Lists available image/video models') and goes further by enumerating the shape of each entry (output type, credit cost, price tier, mode/latency, speed_tier, best_for). It also explicitly distinguishes itself from the generation siblings by saying each 'model' value passes to generate_image or generate_video.

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?

Gives concrete usage context: filter by role or output_type, use sort 'cost' for cheapest first, and pass estimate_only to generate_image/generate_video for an exact quote. It routes the agent to the sibling tools that consume the output, though it does not state explicit when-not-to-use conditions.

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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