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

Annotations already indicate readOnlyHint=true and idempotentHint=true, so the tool is safe. The description adds value by detailing the return fields (resource_id, name, format, datastore availability, last_modified) and the condition on datastore_active for further querying, providing context beyond 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 a single informative sentence followed by an example. No wasted words; every sentence adds value. It is front-loaded with the core purpose.

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 one parameter, no output schema, and comprehensive annotations, the description covers all necessary aspects: input source, output fields, and follow-up usage. It is complete and well-integrated with sibling context.

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 coverage is 100% with a description for the 'id' parameter. The description adds meaning by providing an example usage and linking to neso_search_datasets for obtaining the id, which helps the agent understand where the parameter value comes from.

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 uses a specific verb 'List' and resource 'resources (data files/tables)' and clearly distinguishes from siblings like neso_search_datasets and neso_query_data by stating the input comes from neso_search_datasets and the output is used for neso_query_data.

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 guides the agent to use this tool to list resources before querying data with neso_query_data, and mentions the prerequisite of neso_search_datasets. It implicitly says when to use (to find a resource_id with datastore_active) but does not explicitly state when not to use.

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