list_models

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

With no annotations provided, the description carries the burden of disclosing behavior. It reveals the output format for both MacWhisper and whisper-cpp entries, the conditional presence of whisper-cpp models based on an environment variable, and the requirement that the CLI be reachable. This is substantial behavioral disclosure, though it doesn't cover error scenarios or exact return structure beyond the string formats.

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?

The description is front-loaded with the purpose and then provides necessary formatting details in a structured way. Each sentence adds value for the consumer, though the second and third sentences are somewhat dense. It is not overly verbose for the information it conveys.

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 the tool has an output schema (not shown), the description explains the semantic meaning of the output strings (active marker, engine prefixes) and how to feed them into transcribe_audio. It also covers prerequisites and conditional behavior, making it complete for a list tool with no params.

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 has zero parameters, so the input schema is empty and schema coverage is 100%. The description correctly adds no parameter-specific details. Per the rubric, 0 params warrants a baseline of 4, and there is nothing to add beyond that.

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 opening sentence 'Return the transcription models available across all engines' uses a specific verb ('Return') and resource ('transcription models') with a clear scope. This clearly distinguishes it from sibling tools like transcribe_audio or start_watch, which perform different actions.

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 explains when and how to use the tool: it lists models formatted for use with transcribe_audio, and it notes the prerequisite that the MacWhisper CLI must be reachable even for whisper-cpp. It does not explicitly name alternatives or exclusions, but the context is clear enough for selecting this tool.

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