recommend_spring_sizes

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states that results are 'nearest' recommendations, leaving unclear whether the call is read-only, requires an active document, how similarity is computed, or what the response shape is.

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 single sentence is compact and front-loaded, with no filler. However, it is under-specified for a 16-parameter tool; the structure provides no parameter grouping, examples, or any roadmap for how to pass targets and filters.

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 annotations, no output schema, and a high parameter count, this description is far from complete. It omits return value expectations, parameter combinations, behavior relative to catalogs, and any relationship to sibling spring tools.

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%, and the description names no individual parameters. With 16 optional parameters, an agent cannot determine which target_* dimensions are required or compatible, how filters like tag, catalog_id, or end_type behave, or how limit affects results.

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 names a specific action ('Recommend'), a resource ('nearest spring catalog entries'), and an input concept ('target dimensions'), so the core purpose is clear. However, it does not explicitly differentiate itself from sibling tools like find_spring_sizes or resolve_spring_size, which an agent might reasonably confuse it with.

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 'for target dimensions' implies the tool is meant for dimensional lookup or recommendation, providing a weak usage context. It does not explicitly say when to use this tool over alternatives such as find_spring_sizes or resolve_spring_size, nor does it state any exclusions.

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