inspect_dataset

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

No annotations provided; description discloses input flexibility (ID/slug or name with auto-search) and output fields. However, it lacks details on read-only nature, side effects, or error cases. Adequate but not comprehensive.

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 3-4 sentences in Ukrainian, front-loading the purpose and then listing included fields. No fluff, but slightly longer than necessary due to detail.

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 output schema and no annotations, the description covers input, output contents, and suggests next steps (use get_dataset_data). It is complete for a metadata inspection tool, though error handling is omitted.

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 coverage is 100% with a detailed description for the single parameter. The description adds value by explaining that a name triggers auto-search for best match, going beyond the schema's basic string definition.

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?

Description clearly states the tool provides a detailed card of a dataset including description, manager, license, freshness, and resources. It distinguishes from siblings like find_datasets and get_dataset_data by focusing on inspection before data retrieval.

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?

Description specifies this tool is for inspection before using get_dataset_data, implying a workflow. It does not explicitly mention when not to use or list alternatives, but the context is clear enough for an agent.

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