listen

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

No annotations are provided, so the description carries the full burden for behavior disclosure. It mentions cloud configuration and the JSON return format, but does not disclose recording duration/timeout behavior, microphone permissions, privacy implications of cloud ASR, engine selection, or error handling.

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 the core purpose front-loaded. It contains no filler or redundant information, every sentence adds useful context, and it is appropriately compact.

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?

The description covers the core purpose and output format, but for a tool with two meaningful parameters and no annotations, it leaves important invocation details undocumented (engine choices, timeout semantics, and the distinction from listen_start). The output schema may cover return values, but the input-side guidance is insufficient.

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 property descriptions are entirely absent (0% coverage), and the description never mentions the engine or timeout parameters. The agent cannot infer valid engine values or how timeout affects recognition, leaving the parameters effectively undocumented.

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 clearly states the tool captures local microphone speech and recognizes it as Chinese text, giving a specific verb and resource. It distinguishes from speak (TTS) and health/catalog, but does not differentiate it from the sibling listen_start, so it is clear but not fully positioned among siblings.

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?

It provides setup context: local or cloud ASR is possible, and cloud requires configuring asr.aliyun in config.yaml. However, it does not explicitly state when to use this tool versus listen_start, get_speech, or speak, nor does it give exclusions or alternative conditions.

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