query_stats

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

Annotations provide readOnlyHint=true, and the description reinforces read-only behavior ('Aggregate statistics'). It adds value beyond annotations by disclosing cost (1 token per call) and the nature of results (roll-ups), though does not cover potential missing data or rate limits.

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 two sentences, both essential. The first sentence provides the core purpose; the second adds cost and sibling distinction. No unnecessary words.

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?

No output schema exists, so description must explain return values. It does so adequately (total count, per-category, per-day breakdown). With 0 required params and clear filter descriptions, the tool can be used 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?

All 4 parameters have descriptions in the schema (100% coverage). The description mentions bounding box and date window generally but does not add additional meaning or constraints beyond what's in the schema.

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 aggregates statistics over the signal corpus with specific breakdowns (total count, per-category, per-day trend) and scopes (bounding box, date window). It distinguishes from sibling tool query_signals by noting it returns roll-ups not rows.

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 explicitly compares this tool to query_signals, stating it is cheaper and returns roll-ups, which helps an agent decide when to use this tool over the alternative. It lacks explicit when-not-to-use guidance but provides clear context.

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