stats

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

With no annotations, the description carries the behavioral burden and does disclose the key output behavior: it returns entity/concept counts and the last update timeholme. The word '统计' also clearly implies a read-only query, not a mutation or action.

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?

One short, front-loaded sentence conveys the resource, the operation, and the specific returned data with no filler or redundancy.

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 parameterless, simple statistics tool with no output schema, the description fully conveys what the tool returns and enough context for an agent to select and call it correctly.

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 input schema has zero parameters)Skip, so the baseline of 4 applies; the description has no parametric details to add, and none are needed.

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 action (统计/statistics) applied to a clear resource (知识库/knowledge base) and lists the exact scope: entity/concept counts and last update time. This distinguishes it from sibling list/read tools, which return individual records rather than aggregate stats.

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 implies usage: call this tool when aggregate knowledge base statistics are needed. It does not explicitly name alternatives or exclusion conditions, though no direct sibling appears to offer the same aggregate view, so the guidance is adequate but not explicit.

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