list_datasets

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

The description discloses the metadata fields returned (source, update frequency, row count, key fields, available filters), which is good. However, without annotations, it does not mention rate limits, authentication behavior (beyond the optional api_key), or any pagination/limitations. It's honest but incomplete.

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?

Two concise sentences: first lists the action and metadata, second provides usage guidance. No wasted words; all information is relevant and front-loaded.

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 simple listing tool with one optional parameter and no output schema, the description provides adequate context by listing the metadata fields and recommending it as a first step. It could mention if there is a maximum number of datasets returned, but it's fairly complete.

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%, so baseline is 3. The description adds no additional meaning beyond the schema's parameter description for api_key. It does not explain when or how to use the api_key parameter.

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 'list all available CMS healthcare datasets with metadata', using a specific verb and resource. It distinguishes from siblings like get_data, get_schema, and run_query which focus on data retrieval or schema, not listing.

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?

It explicitly instructs 'Always call this first to understand what data is available', providing a clear usage context. However, it does not explicitly exclude alternatives or mention specific scenarios where this tool would be inappropriate.

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