stats

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

There are no annotations, so the description carries the full burden of behavioral disclosure. The verb '获取' communicates that this is a retrieval/statistics operation, and the listed metrics give some idea of the output content. Still, it does not explain whether the tool reads all stored stories automatically, whether it invokes side effects, or what 'health' means behaviorally.

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 a single compact sentence with a parenthetical list of metrics. It is efficient, front-loaded, and every word adds value. There is no redundant text or unnecessary detail.

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?

Given the tool has zero parameters and no output schema, the description supplies a reasonable preview of the produced statistics. It lists five relevant dimensions and leaves little ambiguity about the tool's role. It could be richer, but for a simple retrieval/stats tool this is sufficient.

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 has no parameters, so the input schema provides no meaningful additional semantics. The description adequately fills this void by indicating what dimensions the statistics cover, which is the only context needed for a parameterless retrieve-stats tool.

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 a specific verb ('获取') and identifies the resource (故事库写作统计), then enumerates the exact kinds of statistics: total words, chapter count, series grouping, health, and repeated phrases. This is distinct from siblings like read_chapter, write_chapter, and validate, making the tool's purpose unambiguous.

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 tool's purpose strongly implies it is used when someone needs write/health statistics for the story library. However, the description does not explicitly explain when to prefer this over alternatives like validate or scan_stories, nor does it provide any exclusions or conditional prerequisites.

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