get_dataset

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

No annotations are provided, so the description must fully disclose behavioral traits. It does mention that refresh_columns triggers a live query to the source database, which is useful context. However, it does not state whether the tool is read-only, require specific permissions, or have any side effects, leaving some gaps in transparency.

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 well-structured with a main sentence followed by parameter details. It is concise but the parameter descriptions could be slightly more streamlined. However, the structure is clear and all sentences are relevant.

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 that an output schema exists and the tool is a simple retrieval operation, the description sufficiently covers what the tool returns (columns, metrics, SQL) and the effect of refresh_columns. No additional context is needed for optimal agent invocation.

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 description adds significant meaning beyond the input schema. For dataset_id, it clarifies it as numeric. For response_mode, it describes each option and the default. For refresh_columns, it explains the behavior and output. Since schema description coverage is 0%, the description fully compensates and provides rich semantic context.

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 the tool retrieves details for a single dataset, including columns, metrics, and SQL. It uses a specific verb ('Get') and resource ('dataset'), and the sibling tools include 'list_datasets' (for listing) and 'query_dataset' (for querying), distinguishing this from those.

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 description explicitly advises 'Use list_datasets first to find valid IDs', providing a clear prerequisite. It also explains the use case for setting refresh_columns=True. However, it does not explicitly mention when not to use this tool or discuss alternatives beyond the prerequisite hint.

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