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LLM Pricing

by io.github.skakumanu
OverviewDiscussionsAdmin

get_use_cases

Get recommended use cases and strengths for LLM models

Input Schema

NameRequiredDescriptionDefault
countryNoOptional ISO-3166 alpha-2 country whose currency to use (e.g. DE -> EUR, IN -> INR). A country whose currency is unsupported yields USD with fallback_to_usd=true.
currencyNoOptional ISO-4217 code to convert prices into, alongside the canonical USD figures. Beats country. Unsupported codes return success=false listing the supported set.
providerNoOptional provider filter

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / country
      Added value: +{
+  "description": "Optional ISO-3166 alpha-2 country whose currency to use (e.g. DE -> EUR, IN -> INR). A country whose currency is unsupported yields USD with fallback_to_usd=true.",
+  "maxLength": 2,
+  "minLength": 2,
+  "type": "string"
+}
    • addedInput schema / properties / currency
      Added value: +{
+  "description": "Optional ISO-4217 code to convert prices into, alongside the canonical USD figures. Beats country. Unsupported codes return success=false listing the supported set.",
+  "enum": [
+    "USD",
+    "EUR",
+    "GBP",
+    "INR",
+    "JPY",
+    "CAD",
+    "AUD",
+    "BRL",
+    "CNY",
+    "SGD",
+    "CHF",
+    "KRW",
+    "MXN"
+  ],
+  "type": "string"
+}
  2. First observed

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. 'Get' implies a read operation, but the description does not disclose return format, filtering behavior, currency conversion effects, or any other operational details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no wasted words. It is appropriately sized for a simple retrieval tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, and the description only broadly indicates that recommendations and strengths are returned. It omits important context implied by the schema, such as price conversion via country/currency and provider filtering.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the country, currency, and provider parameters are already well documented in the schema. The description adds no parameter-specific meaning beyond that baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb and resource: 'Get recommended use cases and strengths for LLM models.' It identifies the content returned, but does not differentiate this tool from siblings such as recommend_model.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives no explicit guidance on when to use this tool versus alternatives like recommend_model or compare_costs. The only implied usage is needing model use cases and strengths, with no exclusions or prerequisites.

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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