List available models with their current pricing. Optionally filter by provider.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max rows to return. Default 200. | |
| provider | No | Provider id, e.g. anthropic, openai, google, venice, openrouter. | |
| include_unavailable | No | Include deprecated/restricted/unavailable models. Default false. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose that this is a read-only operation, auth requirements, rate limits, or pagination behavior. Only the limit parameter hints at pagination, but the description is silent.
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 a single, focused sentence with no wasted words. It is front-loaded with the core action.
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?
Despite having 3 parameters and no output schema, the description is only one sentence. It does not explain return format, pagination details, or what 'available' means. More context is needed.
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?
Schema coverage is 100%, so baseline is 3. The description adds value by noting optional filtering by provider, but does not expand on limit or include_unavailable beyond schema.
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 clearly states the specific verb+resource: 'List available models with their current pricing.' This distinguishes from sibling tools like get_model (single model) or estimate_cost (cost estimation).
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?
The description explicitly mentions optional filtering by provider, giving clear context. However, it does not explicitly state when not to use or point to alternatives like get_model for single model queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools are mostly distinct, but list_deprecations and list_events overlap in covering deprecations. Descriptions clarify that list_deprecations is specific to retirement schedules with runways, while list_events is a broader changelog filterable by severity, so an agent could still choose correctly.
All tool names follow a consistent verb_noun pattern using snake_case (e.g., list_models, get_model, estimate_cost). The length variation is minor and does not break the pattern.
Seven tools is an ideal size for this domain—enough to cover key operations (listing, getting details, checking dependencies, estimating costs, viewing history) without overwhelming the agent. Each tool has a clear role.
The tool set covers the main use cases for model information and monitoring. A minor gap is the lack of a dedicated tool to list providers, though list_models can filter by provider name. Overall, CRUD-like coverage is good for a read-heavy informational server.