Models and limits
get_modelsThe model Kourier serves, its API model string, and context limits.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_modelsThe model Kourier serves, its API model string, and context limits.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is fully covered by structured data. The description adds no behavioral context of its own — no caching, auth, or freshness notes — it only restates the payload contents, so it contributes little beyond the annotations.
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?
A single sentence fragment with no filler; the most important content (the served model and its limits) is front-loaded. It is on the terse side, but nothing is wasted and nothing essential is buried.
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?
With no parameters and no output schema, the description usefully enumerates the three things returned, which is the main gap a caller would otherwise face. It omits return structure and cardinality, but for a trivial read-only lookup this is close to complete.
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 takes zero parameters, so the baseline is 4. The description does not need to explain any inputs, and it adds the useful detail of what the response payload contains (model string, context limits) rather than leaving it entirely opaque.
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 names the specific resource it returns — the served model, its API model string, and context limits — which is enough for an agent to know exactly what data comes back. It is a noun-phrase summary rather than an explicit verb+resource statement, and it does not contrast itself with any sibling, but the purpose is unambiguous.
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?
There is no when-to-use guidance, no prerequisites, and no mention of alternatives. The sibling list (pricing, setup, onboarding, checkout) does not obviously overlap, but the description gives the agent nothing to reason about regarding when this call is appropriate.
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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