get-dataset

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

No annotations provided, so description must cover behavioral traits. It only indicates a read operation ('Get metadata'), but lacks details on side effects, authorization needs, rate limits, or error handling. The return type 'dataset object' is vague.

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?

Description is very short with three sentences and no redundancy. However, it omits important details; brevity is achieved at the cost of completeness.

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 retrieval tool with no annotations or output schema, the description fails to address ambiguity in parameters (both optional, no guidance), error cases, or detailed return structure. Incomplete for reliable agent use.

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 has 0% description coverage and all parameters are optional. The description adds that lookup can be 'by name or ID', but does not specify format, uniqueness, or behavior when both are provided. No constraints or examples for parameter values.

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 'Get dataset metadata by name or ID', specifying verb and resource. However, it does not distinguish itself from sibling tools like get-dataset-examples or get-dataset-experiments, which target specific subsets of dataset 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?

No guidance on when to use this tool versus alternatives (e.g., get-dataset-examples). The example is generic and does not clarify when to prefer this over other dataset-related tools.

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