get_dataset_column_detail_v1_datasets__provider___dataset__colum

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

Discloses return of full value list up to 1000 for low-cardinality columns, but doesn't specify behavior for high-cardinality columns, auth requirements (beyond 'public'), or error cases. With no annotations, more detail would be beneficial.

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?

Two concise sentences, first stating purpose, second adding a key behavioral detail. No wasted words, front-loaded with core 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?

No output schema, so description must cover return values. It does mention the value list, but omits details on what 'detailed statistics' include. Lacks pagination info. Still mostly complete for a straightforward retrieval tool.

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?

Parameters (provider, dataset, column_name) are self-explanatory from names, but schema coverage is 0% and description adds no additional constraints or format details. Baseline 3 for adequate but minimal value.

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?

Clearly states it retrieves detailed statistics for a single column, with specific mention of returning value list for low-cardinality columns. Distinguishes from sibling tools like get_dataset_columns and get_dataset_stats.

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 explicit guidance on when to use this over alternatives. Siblings exist for listing columns or dataset stats, but description doesn't compare or set usage context. Only implies public access.

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