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

Annotations already cover readOnly/idempotent/openWorld, so the description focuses on adding context: the government-gauge source, one reading per day, and the exact statistics returned with their dates. It does not mention rate limits, failure modes for unknown lake names, or pagination, but nothing contradicts 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?

Two sentences, zero waste: the data shape and scope come first, the usage hint last. Every clause carries information an agent needs.

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?

With no output schema, the description usefully names the returned aggregates (first, last, low, high, mean with dates) and the source gauge, which is what an agent needs to report results. Minor gap: no guidance on how an invalid or ambiguous lake name is handled.

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 all three parameters are already documented, including the daily/weekly enum semantics and the 2-365 range. The description reinforces the day range and step choice but adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb+resource (daily/weekly water elevation series) with scope (US lake or reservoir, 2-365 days) and explicitly ties the data source to the sibling get_lake_level. An agent can distinguish it from get_lake_level, search_lakes and compare_lakes without reading the schema.

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?

Names concrete use cases ("trends, drawdown and refill questions") and implicitly routes point-in-time reads to get_lake_level by referencing the same gauge. It stops short of explicitly stating when not to use it (e.g. current level, multi-lake comparison), so exclusions are left to inference.

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