Unified card for one model in a single call: normalized pricing, capabilities (context window, vision, reasoning, tags), availability, reseller markup vs. upstream, and a price-history summary (launch vs. current price, percent change, last change date, all-time low/high).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Model id in provider/model form, e.g. openai/gpt-5-5. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Clearly lists returned data: normalized pricing, capabilities, availability, reseller markup, price-history summary. Does not mention destructive behavior or auth, but implies read-only operation.
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?
Single sentence packs detailed information efficiently. Slightly long but no wasted words. Could be split for readability, but current structure is acceptable.
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?
No output schema, so description must explain return values. It comprehensively lists components: pricing, capabilities, availability, markup, price history (including launch vs current, percent change, dates, all-time high/low). Covers complexity well.
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% with one parameter 'id' described as 'Model id in provider/model form'. Description adds no additional semantics beyond schema, so baseline 3.
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?
Description specifies 'Unified card for one model in a single call' with clear verb and resource, and distinguishes from sibling tools like list_models (multiple models) and get_price_history (history only).
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?
States when to use (getting comprehensive single-model data) but does not explicitly exclude cases or mention alternatives beyond implied context. Lacks explicit 'when not to use' guidance.
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.