list_transcription_models

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

With no annotations, the description must carry the behavioral load, and 'List' implies a read-only, non-destructive operation, which is reasonable. However, it says nothing about authentication requirements, whether a live API key is needed, pagination, or result ordering.

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, front-loaded sentence with no filler. The scope qualifier ('that support audio transcription') is the one piece of information that distinguishes this list from a generic model listing, and it is stated directly.

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?

For a parameterless read-only listing tool with no output schema, the description is close to sufficient. The only real gap is that it doesn't hint at what the returned entries contain (e.g., model identifiers usable in transcribe_audio), which an agent would need to chain the two calls.

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 and the schema is empty, so there are no parameter semantics to document. The baseline for a zero-parameter tool is a 4; the description adds nothing here because nothing is required.

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?

States a specific verb (List) and resource (OpenRouter models) with a scope qualifier (support audio transcription). An agent can tell it apart from the sibling transcribe_audio, which performs transcription rather than discovery, though the description never names that sibling explicitly.

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 explicit when-to-use guidance, no prerequisites, and no mention of the transcribe_audio sibling as an alternative. Usage is only weakly implied by the fact that a preceding model-discovery step would logically precede a call to transcribe_audio.

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