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

With no annotations provided, the description carries the behavioral disclosure burden. It adds useful context beyond the obvious read operation: data is published daily, reservoir levels are from a specific 5 AM measurement, notices are translated, and attribution to 787daily.com and AAA is required. This gives an agent meaningful expectations about freshness, sourcing, and processing without contradicting any annotation.

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 a single dense sentence that front-loads the core purpose and then enumerates the components and attribution requirement. Every clause adds useful information, though the long parenthetical-heavy structure makes it slightly less scannable than an ideal description.

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 no output schema, the description does well to enumerate what the agent should expect: rationing plan details, reservoir levels with alert bands, trend/pace analysis, and translated notices. It also covers source attribution and data freshness. It does not explain the optional reservoir parameter's effect on the response, but the schema fully covers that.

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?

The input schema already documents the only parameter ('reservoir') with a clear description and example slugs, so schema coverage is 100%. The tool description does not mention the optional filter, but it does not need to; the schema carries that 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?

The description clearly identifies the resource ('Puerto Rico's water situation right now') and enumerates the specific data delivered: AAA's metro rationing plan, reservoir levels with alert bands, trend/pace analysis, and translated utility notices. This content list distinguishes it from siblings like get_reservoir_levels, which appears to cover only reservoir 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 phrase 'right now' and the focus on today's 5 AM levels and latest notices make the intended use clear: retrieving the current water status snapshot for Puerto Rico. It does not explicitly say when not to use it or point to an alternative like get_reservoir_levels, but the context is sufficiently clear.

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