List Models

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

With no annotations, the description carries the full burden and does useful work: it discloses that whisper-cpp entries only appear when MACWHISPER_WHISPERCPP_MODEL_DIR is configured and warns that the MacWhisper CLI must be reachable even if only the whisper-cpp engine is intended. It does not cover failure modes or what happens when the CLI is unreachable, so not a full 5.

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?

Purpose is front-loaded and the two engine formats are clearly separated, but a large share of the text re-describes the output string format even though an output schema already exists, making it longer than the tool's single-action nature warrants.

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 zero-parameter, read-only listing tool with an output schema, the description is more than complete: it explains the engine-specific formatting, the environment-variable dependency, and the CLI reachability requirement an agent needs in order to use results correctly.

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, which sets a baseline of 4, and the description appropriately uses its space to explain how the returned identifiers feed the parameters of other tools rather than inventing input semantics that do not exist.

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 ('Return') and resource ('the transcription models available across all engines'), with the scope made explicit. An agent can immediately distinguish this discovery tool from the sibling action tools like transcribe_audio and cancel_transcription.

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?

The description clearly explains the context of use by tying the returned strings back to the 'model' and 'engine' arguments needed for transcription, so an agent knows this is a prerequisite discovery step. It stops short of naming alternative tools or explicit when-not-to-use conditions, so it does not reach a 5.

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