List models
list_modelsList the AI video models VidFare tracks, with the cheapest current dollars per second for each.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
list_modelsList the AI video models VidFare tracks, with the cheapest current dollars per second for each.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds useful context that prices are 'cheapest current' and denominated in dollars per second, but says nothing about result ordering, size, or freshness beyond the word 'current'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single well-formed sentence with the resource front-loaded and the payoff (cheapest dollars per second) trailing. No filler, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter, read-only listing tool with no output schema, the description conveys enough about what comes back (model list plus per-second price) to call it correctly. Minor gaps remain around ordering and whether all models or only priced ones are returned.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. No parameter concerns are introduced.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb (list) and resource (AI video models tracked by VidFare) and previews the payload (cheapest current dollars per second per model). It is clear without opening the schema, though it doesn't explicitly contrast itself with siblings like get_model_prices or cheapest_options.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied: the zero-parameter shape and 'tracks' wording suggest a catalog/discovery call, but there is no explicit statement of when to choose this over get_model_prices or cheapest_options. An agent must infer the routing.
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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