get_dataset

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Get details' but doesn't clarify if this is a read-only operation, what permissions are needed, whether it returns structured metadata or raw data, or any rate limits. This leaves critical behavioral traits unspecified for a tool with potential data access implications.

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, efficient sentence ('Get details of a specific dataset.') that is front-loaded and wastes no words. It directly conveys the core purpose without unnecessary elaboration, making it highly concise and well-structured for quick understanding.

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 the complexity of data retrieval tools and the lack of annotations or output schema, the description is incomplete. It doesn't explain what 'details' entail (e.g., JSON metadata, statistics), how errors are handled, or what the return format is. For a tool that likely returns structured data, this omission leaves significant gaps in understanding its full 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?

The input schema has 100% description coverage, with 'dataset_id' documented as 'Dataset ID or username~dataset-name'. The description adds no additional meaning beyond this, such as examples of valid IDs or how to resolve conflicts. With high schema coverage, the baseline score of 3 is appropriate, as the schema already provides adequate parameter semantics.

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 'Get details of a specific dataset' clearly states the verb ('Get') and resource ('dataset'), but it's vague about what 'details' includes (e.g., metadata, structure, size). It doesn't differentiate from siblings like 'list_datasets' (which lists multiple datasets) or 'get_dataset_items' (which retrieves content items), leaving the scope ambiguous.

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 is provided on when to use this tool versus alternatives. For example, it doesn't specify if this is for metadata retrieval versus data access, or when to prefer 'get_dataset_items' for actual content. The description implies usage for a single dataset but offers no exclusions or prerequisites.

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