stats

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

With no annotations, the description fully carries the behavioral disclosure burden. It communicates a read-only operation via the verb 'read,' but lacks additional traits such as performance implications, return format, or side effects. This is minimal but viable for a simple stats tool.

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, front-loaded sentence with no redundant words. Every word contributes to the purpose, making it exceptionally concise.

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 zero-parameter, read-only nature, the description covers the core behavior. However, without an output schema, the terms 'canonical watermark statistics' are not elaborated, leaving a minor gap in understanding what the returned stats actually contain.

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 zero parameters, so the description does not need to explain parameter semantics. The baseline for 0 params is 4, and the description provides no unnecessary parameter details.

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 reads 'local index status and canonical watermark statistics,' using a specific verb and resource. This distinguishes it from sibling tools like fact_get and document_get, which target different data types.

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 for checking index status and watermark statistics but provides no explicit context, exclusions, or comparisons to alternatives. There is no guidance on when to prefer this tool over siblings like health or timeline, so it meets the baseline for implied usage.

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