insights

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

With no annotations, the description carries the full burden; it does so by explicitly framing the operation as a read of the caller's own data, implying read-only behavior and scoping. It does not mention caching, latency expectations, or auth, but those are not critical for this simple stats read.

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?

A single sentence with no filler. The primary use case is front-loaded and the three returned metrics are listed compactly, so every word earns its place.

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 zero-parameter read tool with an output schema, the description is nearly complete. It could have added a sentence about when not to use it or how it differs from status, but the core invocation information is fully present.

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 and an empty input schema, so the baseline is 4. There is nothing for the description to add beyond confirming no arguments are needed, which it does implicitly by listing outputs rather than inputs.

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 uses a specific verb ('read') and a specific resource ('your own recall stats'), then names the exact metrics it returns: query volume, latency, and recall mix. This makes it distinct from sibling tools like status or show, even without explicitly naming them.

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 opening 'Use to read your own recall stats' clearly states the intended context and audience (the caller's own statistics). It does not list exclusions or alternatives, but for a simple read-only introspection tool the context is sufficient.

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