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Compare lake levels

compare_lakes
Read-onlyIdempotent

Current levels of 2 to 10 US lakes side by side, read live from their gauges: elevation, feet below full pool, percent full, seasonal target and 24 h / 7 day / 30 day change, ranked by distance below full pool. A lake whose gauge is down is reported with its error instead of failing the whole call.

Input Schema

NameRequiredDescriptionDefault
lakesYesSlugs or names, for example ["lake-mead", "lake-powell"].

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already cover read-only, idempotent and open-world traits, but the description adds substantive behavior: data is live-read from gauges, results are ranked by distance below full pool, and a dead gauge returns its error rather than failing the whole call. That partial-failure semantics is exactly the kind of disclosure an agent cannot get from annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with a colon-delimited field list and a trailing caveat; every clause carries information. Slightly dense but no padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description does the work of enumerating returned metrics (elevation, feet below full pool, percent full, seasonal target, 24h/7d/30d change), ranking order, and per-lake error handling. Only the exact response shape/wrapping is left unspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the description adds little beyond it — '2 to 10 US lakes' restates minItems/maxItems, and the slug-vs-name flexibility is already documented on the `lakes` items. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb ('compare') and resource (US lake gauge levels), including the batch scope (2 to 10 lakes). It is clearly distinct from siblings get_lake_level (single lake) and search_lakes (discovery), so an agent can route without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 2-to-10-lake batch and the side-by-side framing imply this is the multi-lake alternative to get_lake_level, but no sibling is named and no when-not-to-use condition is stated. Usage is inferable rather than explicit.

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

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