query_hotspots

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

The annotations indicate destructiveHint: true, but the description describes a read-only query operation that returns grid-binned data and metadata. This is a direct contradiction. According to the rubric, a score of 1 is required when the description contradicts annotations. The description does disclose token cost and the unit of cell counts, but the safety profile mismatch is a serious inconsistency that undermines trust.

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 concise and well-structured: it starts with the core purpose, includes a usage phrase, provides a clarifying note about the unit and accountability of counts, and mentions the token cost. Every sentence earns its place, and the note is valuable for interpreting results correctly.

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?

The description is quite complete for a query tool with an output schema: it explains what the tool returns (peak severity, categories, event_ids), clarifies the unit of cells, and discloses cost. However, the complete absence of any mention of the tool's safety profile (aside from the misleading destructiveHint) is a gap that could confuse an agent. The description supplies most necessary context, but the contradiction with annotations prevents a perfect score.

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?

Schema description coverage is 100%, so the baseline is 3. The schema already provides thorough descriptions for all parameters, including the nuanced 'limit' parameter. The tool description adds context about what the cells count (satellite-observable points) but does not add parameter-specific meanings beyond the schema. Hence, it stays at the baseline.

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's verb and resource: 'Geographic hotspots — signal density grid-binned into cells, ranked by event count, each with peak severity, the categories present, and up to 5 representative event_ids'. It also provides a usage orientation ('Use to find WHERE activity is concentrating'), which differentiates it from sibling tools like query_signals (which likely returns raw signals) and query_stats (aggregate statistics).

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 gives a clear use case: 'Use to find WHERE activity is concentrating.' It does not explicitly name alternatives or exclusions, but the context signals list sibling tools, and the purpose is clear enough for an agent to choose this tool for spatial density analysis. The guidance is clear but lacks explicit 'when-not-to-use' or alternative names.

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