Per-model token rate card ($/1M input, output, cached input, context window) for a token-priced AI product, plus a cost estimate when a token volume is given.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Product slug, e.g. "openai", "claude", "gemini". | |
| model | No | Model id to select, e.g. "gpt-5.4". Optional. | |
| inputTokens | No | Input token count for the estimate. | |
| outputTokens | No | Output token count for the estimate. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior fully. It explains the tool returns rate card data and optionally an estimate, implying it is a read-only query. No destructive behavior is suggested, and the purpose 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 a single sentence that captures the core functionality without any extraneous words. It is front-loaded with the primary action ('Per-model token rate card') and clearly separates the two modes (with and without token volume).
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?
While the description covers the basic purpose, it lacks details about the output structure (e.g., what fields are returned in the rate card) and does not mention any side effects or prerequisites. For a tool with no output schema, this is a minimum viable description but leaves uncertainty for an AI agent.
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%, but the description adds context by explaining the return type (rate card and estimate) and the optional nature of token inputs for cost estimation. This goes beyond the schema descriptions which only name the parameters.
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 tool provides per-model token rate cards and optionally computes cost estimates. This distinguishes it from sibling tools like get_pricing (which may cover broader pricing) and calculate_tco (which likely deals with total cost of ownership).
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?
No guidance is given on when to use this tool versus alternatives like calculate_tco or get_pricing. The description only states what it does, not when it's appropriate or when to avoid it.
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.
Each tool has a clearly distinct purpose: from TCO calculation to comparison, discovery, LLM cost estimation, negotiation guides, hidden costs, positioning, price history, and full pricing records. No two tools overlap significantly; they complement each other.
All tool names follow a consistent verb_noun pattern with lowercase and underscores, primarily using 'get_' for five tools and other specific verbs like 'calculate', 'compare', 'discover', 'estimate'.
With 9 tools, the server is well-scoped for a pricing analysis domain, covering essential queries without being overwhelming or sparse.
The tool surface comprehensively covers the pricing domain: discovery, comparison, detailed pricing, hidden costs, TCO, price history, positioning, and negotiation advice. No obvious gaps are present for the intended use case.
