search_cubes

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

While annotations already indicate read-only, open-world, and idempotent behavior, the description adds non-obvious context: 'By default only the newest published version of each cube is returned; set latest_only=False to see every version.' It also clarifies query matching semantics against names and descriptions in the chosen language, going well beyond the structured annotations.

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 compact and well-structured: a one-sentence purpose, a workflow note, a behavioral default, then a terse Args list. Every sentence contributes value, with no redundancy or fluff, making it easy for an agent to scan and retain.

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 5 parameters and an output schema, the description covers the tool's role, integration with siblings, all parameter semantics, and key version-collapse behavior. The output schema handles return values, so no further explanation is needed. The description is fully adequate for correct selection and invocation.

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. It does so with a dedicated Args block explaining every parameter, providing example values for query, the source for creator_uri, a range for limit, and the meaning of latest_only. This adds substantial meaning beyond the bare schema titles.

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 opens with 'Find statistical data cubes in LINDAS by topic,' clearly stating the verb, resource, and scope. It further distinguishes itself from sibling tools by noting that it returns cube URIs to be passed to get_cube_structure, establishing a specific role.

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 explicitly labels the tool 'The entry point' and instructs that returned URIs should be passed to get_cube_structure, creating a clear workflow. It also mentions that creator_uri comes from list_publishers, tying the tool to its siblings and giving practical when-to-use guidance.

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