usgs_water_statistics

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context beyond annotations: it aggregates statistics across ALL years on record, computes percentiles, and optionally filters by month/day. This enriches the agent's understanding of the operation without contradicting the annotations.

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 compact and well-organized: it opens with the core purpose, then a practical use-case note, then parameter specifics. Every sentence adds value—no filler. The structure front-loads the most important information and keeps the parameter details at the end, making it easy to scan.

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 tool's complexity (5 parameters, no output schema), the description covers the essential aspects: the statistics returned, the aggregation scope, the use case, and the key parameter options. It does not describe the exact output format, but that may be acceptable without an output schema. The description is adequate for an agent to correctly invoke the tool, though a bit more detail on return structure would push it to a 5.

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 coverage is 100%, so every parameter already has a description. The tool description adds value by explaining parameter codes (00060=discharge, 00065=gage height) and noting that month/day filtering is optional. It also clarifies that the default stat_report_type is daily, which aligns with the schema. This goes beyond the schema's basic descriptions, earning a score above the baseline 3.

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 function: retrieving period-of-record streamflow statistics for a USGS site, including min/mean/max and p05-p95 percentiles per day-of-year. It goes beyond a generic verb+resource by specifying the exact statistics and the aggregation across all years. It also distinguishes itself from raw readings, which is a useful differentiator among siblings like usgs_water_data.

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 frames the use case: 'is the current flow historically high or low for this date?' and notes it is 'far more analytically useful than raw readings for drought/flood context.' This provides a clear scenario for when to use this tool. However, it does not explicitly mention when not to use it or name alternatives among the many USGS siblings, so it stops short of a full when/when-not comparison.

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