compare_soil_depths

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

No annotations are provided, so the description carries full burden of behavioral disclosure. The description only states the operation ('compare aligned series') but doesn't disclose what 'aligned' means, whether this is a read-only aggregation operation, what happens with missing depths, how multi-depth data is combined, or any performance considerations. The tool likely produces a derived/computed output, but no behavioral detail is disclosed.

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?

A single concise sentence with no wasted words. It's appropriately short given that it offers little content. However, conciseness at the cost of completeness means the brevity isn't earned—there's substantial missing information that could have been compressed into a still-compact but more complete 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?

Despite having an output schema and 8 parameters (3 required), the description addresses none of the tool's complexity. It doesn't explain what the comparison produces, how depths map to series, what 'aligned' means operationally, what operations are available, or how the metric/data_type/interval parameters behave. Even with the output schema present, the description is inadequate for an 8-parameter comparison tool.

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 description coverage is 0%, so the description carries the full burden of explaining parameters. With 8 parameters including metric, interval, data_type, depths_cm, and operation, the description provides zero elaboration on any of them. The term 'aligned' hints at alignment logic but doesn't explain the operation parameter (avg) or how depths_cm filtering works, metric selection, or data_type semantics. This is a significant gap.

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 'Compare aligned soil-moisture or temperature series across sensor depths' clearly identifies the verb (compare), resource (soil series), and scope (across sensor depths). It distinguishes from siblings like get_observations (fetch raw series) and aggregate_observations (aggregate observations), though it doesn't explicitly name alternatives. The purpose is specific to depth-based comparison, differentiating it from other observation tools.

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?

No when-to-use guidance is provided. The description doesn't say when to use this over get_observations, aggregate_observations, or describe_dataset. It implies a comparison use case but gives no exclusions or alternative tool references. Given 9 siblings, the lack of guidance is a clear gap.

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