discover-datasets

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

The verb 'List' communicates a read-only enumeration action, and 'all available' suggests completeness. However, with no annotations at all, the description does not disclose the return format (e.g., names, IDs, metadata), required permissions, or any other behavioral constraints. The core behavior is clear, but additional disclosure would strengthen it.

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, direct sentence with no fluff or repetition. It front-loads the action and resource clearly, making it easy for an agent to parse quickly.

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 zero parameters and no output schema, the description is mostly sufficient for calling the tool: the agent knows the action and target resource. It could be slightly more complete by clarifying what a 'dataset' contains and how this relates to sibling analytics tools, but the low complexity keeps this from being a major gap.

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 tool has zero parameters, so there is no parameter semantics to document. The schema already fully covers this, making the description's lack of parameter detail acceptable. Baseline for zero-parameter tools applies.

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 ('all available BambooHR datasets'), and adds the qualifying context 'for analytics queries'. It clearly states what the tool does, though it does not explicitly distinguish itself from the similarly-named sibling 'discover-fields'.

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 phrase 'for analytics queries' implies this is the tool to use when you need to see available analytics datasets, but there is no explicit guidance about when to prefer this over siblings like discover-fields, list-custom-reports, or workforce-analytics. Usage context is implied rather than explicit.

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