list_analytical_datasets

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

No annotations are provided, so the description must carry the burden. It states the tool lists and returns data, implying a read-only operation, but does not disclose any behavioral traits such as permission requirements, rate limits, or side effects. For a simple list tool, this is adequate but not fully transparent.

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 two sentences, front-loaded with the main purpose, and each sentence adds value: first sentence states the action, second sentence elaborates on return details. No superfluous content.

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 the lack of output schema, the description partially explains return values (names, types, URLs). It does not cover pagination or error conditions, but for a list tool with well-documented parameters, it is reasonably complete. Could be improved with usage guidance.

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 100%, with descriptions for space_id, asset_id, top, and skip. The description adds no additional meaning beyond the schema (e.g., 'within a specific asset' aligns with asset_id). Baseline 3 is appropriate.

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 lists analytical datasets within a specific asset, distinguishing it from siblings like list_catalog_assets or get_analytical_metadata. The verb 'list' and resource 'analytical datasets' are specific.

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 implies usage when you need to discover analytical models for an asset, but it does not explicitly state when to use this tool versus alternatives like list_catalog_assets or query_analytical_data. No when-not-to-use guidance is provided.

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