list_modelsLists available model IDs for choosing a valid model argument, showing tier-carrying IDs and noting bare IDs are accepted even when not listed.
List models for model argument. Returns models (raw agy models output) and model_ids (parsed ids). CLI lists tier-carrying ids only; bare ids like gemini-3.8-flash are valid for model but not in list.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.4.0Input schema / additionalPropertiesAdded value: +falsev0.2.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses return values (models raw output, model_ids parsed ids) and a key behavioral caveat: the CLI lists only tier-carrying ids, while bare ids are valid but omitted. It does not explicitly state read-only safety, but the nature of a list operation is clear.
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?
The description is three sentences, front-loaded with the purpose, then return details and a crucial caveat. Every sentence adds value without waste.
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 zero-parameter, annotation-free tool with no output schema, the description explains the action, return values, and an important limitation. Nothing essential for an agent to call it correctly is missing.
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 has zero parameters, so the schema baseline is 4. The description references a 'model argument' but that is not a parameter of this tool; no additional parameter semantics are needed.
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 states a clear verb (List) and resource (models) and contextualizes it for the model argument. It does not explicitly differentiate from sibling tools like list_agents, but the resource is distinct enough for an agent to identify its purpose.
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?
It provides clear context: use this to find models for the model argument, and explains that the returned list may not include all valid bare ids. No explicit when-not or alternatives are given, but the intended usage is implicit and sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.