transcribe_audio

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

With no annotations provided, the description carries the full burden. It fully discloses key behaviors: automatic chunking for long audio, sliding window concurrency, context passing, and return of timing segments. No contradictions with annotations.

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 well-structured with a one-sentence purpose, a support list, feature bullets, Args, and Returns. Every sentence adds value, and it is easy to scan. No fluff.

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 moderately complex tool with no output schema, the description covers supported formats, behavior for long audio, parameter modes, concurrency limits, and the return type. It could add more detail on the structure of timing segments or error handling, but it is complete enough for tool selection and invocation.

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 coverage is 100%, so baseline is 3. The description adds value beyond the schema by explaining trade-offs and recommendations for context_mode (e.g., 'sliding' recommended, 'full_serial' best quality but slow) and clarifying the purpose of max_concurrency. This enhances semantic understanding.

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: 'Transcribe an audio file to text using AutoGLM ASR.' It clearly distinguishes from sibling tool get_audio_info by focusing on transcription rather than audio metadata.

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 provides clear context for when to use this tool (any transcription need) and gives detailed parameter guidance (e.g., recommended context_mode). It doesn't explicitly mention alternatives or when not to use the tool, but the sibling tool is obviously different, so the context is sufficient.

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