list_data_sets

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

No annotations are provided, so the description is the sole source for behavioral traits. It fails to disclose whether the tool is read-only, idempotent, or any rate limits or authentication requirements. The word 'List' implies read-only but is not explicit.

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 concise sentences. The first sentence states the action and output, and the second provides a use case. No redundant or irrelevant information.

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 and an output schema (assumed to cover return values), the description is somewhat complete but lacks details on parameter usage and behavioral guarantees. It covers the basic purpose but not the nuances of filtering or pagination.

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?

The input schema has 2 parameters with 0% description coverage. The description does not explain what the 'limit' and 'query' parameters do or how to use them, leaving the agent without crucial context for proper invocation.

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 that the tool lists datasets (data entry forms) and specifies the information returned (period type and data elements). It also provides a usage hint to discover aggregate data, distinguishing it from sibling tools like list_org_units or list_programs.

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 says 'Use this to discover what aggregate data the instance collects,' which gives a clear context for when to use it. However, it does not mention when not to use it or compare with alternatives like search_metadata.

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