notes_stats

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

With no annotations and no output schema, the description carries the full burden. It does disclose what is computed and notes that tag distribution comes from parsing #tag in the body, which is useful behavioral detail. It does not address cost (e.g., whether it scans all notes), whether it operates on all notes or a subset, or the shape of the returned data.

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?

Two short sentences with no wasted words, and the output content is front-loaded. The second sentence adds usage context efficiently, though it is slightly vague about what '语料规模' entails.

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 simple no-parameter statistics tool, the description is adequate but incomplete. It lists the metrics returned but, without an output schema, does not describe the structure of the response (e.g., how tag distribution is formatted), so an agent cannot fully predict the return shape.

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 takes zero parameters, so the baseline is 4. There is nothing extra to document, and the description does not need to compensate for missing parameter information.

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 states a specific purpose: returning aggregate corpus statistics (note count, word count, tag distribution, last-modified time). It does not explicitly name or contrast with the siblings search_notes, read_note, or list_recent, but the aggregate nature makes it obviously distinct from those tools.

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 phrase '用于先摸清语料规模' gives a clear implied usage context: use this first to gauge the size of the corpus. However, it does not explicitly state when not to use it, nor does it name alternatives or prerequisites.

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