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

Annotations already declare read-only, idempotent, non-destructive, closed-world behavior, so the safety bar is low. The description adds genuine context beyond that: the catalog is fixed at 44 entries drawn live, and each result carries slug, full-pool elevation, gauge agency and page. Rate limits or freshness caveats are absent, but for a static-ish catalog read that is minor.

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, front-loaded with the verb and scope, then the return shape, then the no-argument default. No filler or restatement of the title.

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 the description carries the return-value burden and does so by listing the four returned fields, plus the catalog size, filterable facets and zero-argument behavior. Nothing an agent needs to call this correctly is missing.

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?

With 100% schema coverage the baseline is 3, and the description earns above it by broadening the query semantics to lake, river, operator or state, and by noting the case where no arguments are supplied. The schema's own query text mentions only lake/river/dam names, so "operator" is real added meaning.

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?

Names a specific verb (list) and resource (the 44 US lakes and reservoirs this server reads live), enumerates concrete examples, and states the searchable facets and returned fields. An agent can immediately tell this is the discovery/enumeration tool rather than a data-fetching one.

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?

"Call with no arguments to list them all" gives explicit default behavior, and the filter facets imply how to narrow. It stops short of naming get_lake_level or compare_lakes as the follow-on alternative once a slug is known, so routing guidance is implied rather than stated.

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