list_model_routes

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

With no annotations, description carries full burden and discloses key behaviors: no model calls, no API key exposure. This is sufficient for a read-only diagnostic tool, though it doesn't mention auth or performance impacts (likely negligible).

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?

Two short, focused sentences with no redundancy. The first sentence gives the core action, the second adds critical qualifiers without extra words.

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?

Given low complexity (1 optional param, no output schema), the description covers purpose and behavior well. The only gap is the missing parameter explanation, which is minor since the parameter is optional and default null.

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 has one parameter (panel) with no description, and the tool description does not explain it. With 0% schema description coverage, the description should compensate but fails to clarify what 'panel' does or how it affects output.

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 clearly states the tool shows how model specs resolve to providers or endpoints, provides concrete examples (bare model strings vs endpoint refs), and distinguishes itself as diagnostic only. This makes the purpose specific and 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?

Explicitly states it is a diagnostic tool only, does not call models, and never returns API keys, giving clear context for when to use. However, it doesn't compare to siblings like list_adapters or list_defaults, missing full guidance on alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.