get_high_tide_flooding_seasonal

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Get' implies a read operation, it doesn't address important behavioral aspects: whether authentication is required, rate limits, error handling, response format details, or data freshness. For a tool with 8 parameters and no output schema, this leaves significant gaps in understanding how the tool behaves.

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 perfectly concise - a single sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded with the core functionality and wastes no space on redundant information. Every word earns its place in this efficient formulation.

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?

For a tool with 8 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what 'seasonal count data' means in practice, how the results are structured, or provide any context about the data source or limitations. The agent must rely entirely on the input schema for parameter understanding and has no guidance about output format or content.

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 description adds minimal value beyond what the schema already provides. With 100% schema description coverage, all parameters are well-documented in the schema itself. The description mentions 'seasonal count data' which hints at the 'season_months' parameter's purpose, but doesn't provide additional context about parameter interactions or usage patterns beyond what's in the schema descriptions.

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 purpose: 'Get high tide flooding seasonal count data for a station'. It specifies the verb ('get'), resource ('high tide flooding seasonal count data'), and scope ('for a station'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_high_tide_flooding_annual' or 'get_high_tide_flooding_monthly', which prevents a perfect score.

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 provides no guidance on when to use this tool versus alternatives. With multiple sibling tools for high tide flooding data (annual, daily, monthly, likelihoods, projections), the agent receives no help in selecting this seasonal count tool over others. There's no mention of use cases, prerequisites, or comparative context.

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