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

With no annotations at all, the description carries the full burden and does so well: it discloses the 180-second chunking and concatenation behavior, that output is plain text without timestamps, the hard limits (2 hours, 500MB), per-hour billing based on actual duration, and that insufficient balance causes rejection at submission. Those are exactly the facts an agent needs to predict success, cost, and the shape of the result.

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?

Front-loaded with the core purpose and limits, then the processing behavior, then the follow-up tool, then parameter guidance, then billing. Every sentence carries a constraint or a routing hint, though the heavy parenthetical stacking makes it denser than it needs to be.

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 4-parameter async mutation tool with an output schema (so return values need no explanation), the description covers limits, processing semantics, follow-up polling, parameter meaning, and failure modes such as balance rejection. Only file_name is left undocumented, a minor omission given the rest of the coverage.

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 description coverage is 0%, so the description must compensate, and it explains three of four parameters: language (blank = auto-detect, otherwise a code like zh/en), context (comma-separated hot words for names/terminology/brands, applied to all segments), and implicitly audio_url through the format and size limits. The file_name parameter is never mentioned, which is the remaining gap.

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?

Names a specific verb and resource (submit a long-audio transcription task) and pins the scope precisely: meetings/podcasts/online courses, ≤2 hours, ≤500MB, six accepted formats. The word '长音频' plus the async polling instruction distinguishes it from the short/real-time siblings such as transcribe_audio without the agent needing to open any schema.

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?

Gives concrete when-to-use context (long recordings, meeting/podcast/course content) and an explicit next step: poll results with get_transcription_task. It stops short of explicitly excluding the sibling short-audio or speech-task tools, so the choice between submit_transcription_task and transcribe_audio is only implied by the length/duration framing.

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