crispasr_detect_language

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

No annotations are present, so the description carries the behavioral disclosure burden. It does this reasonably well by stating the output values, the prerequisite of a local LID model path, and the recommended backend. It does not describe failure modes, exact return formatting, or model-resolution behavior, but the core runtime behavior is clear.

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 three short sentences with no filler. The main action is front-loaded, followed by return semantics, then prerequisites and a recommendation. Every sentence earns its place.

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 tool with no annotations and no output schema, the description covers the core operation but leaves some gaps: it does not specify the exact output structure, accepted media file types, or how this tool relates to sibling model-management tools like crispasr_download_models and crispasr_resolve_model_paths. It is functional but not fully 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 schema has 0% description coverage, but the description compensates by mapping 'media file' to file_path, 'local LID model path' to lid_model, and 'firered backend is recommended' to lid_backend. It does not mention crispasr_bin, but this is an optional parameter and the required parameters are semantically covered.

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 opens with a specific verb and resource: 'Run language detection on a media file using CrispASR LID.' It also states the return value, detected language plus routing decision, and is clearly distinct from transcription-focused siblings like transcribe_audio and transcribe_video.

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 implies this tool is for language detection and routing to english/chinese/uncertain, but it does not explicitly say when to use it instead of transcription tools or mention alternatives. The local LID model path requirement and recommended firered backend are useful setup guidance but not usage-scenario guidance.

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