Query Dataset

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

Annotations already declare readOnlyHint/openWorldHint/destructiveHint=false, and the description is consistent with them, adding the important enforcement detail that only SELECT/WITH statements are accepted. It also discloses the extra_paths table-registration and collision fallback behavior (dataset2/dataset3), which the agent could not infer otherwise. It does not discuss error behavior or result-size truncation, keeping it below a 5.

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?

Front-loads the core action and constraint in the first sentence, then adds the table-naming rule and a worked example, each of which earns its place. Dense but not padded; a short pointer to the paging parameters is the only missing piece.

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?

An output schema exists, so return values needn't be spelled out, and the description still helpfully notes that the response includes a tables name->path map. Combined with the SELECT/WITH restriction and extra_paths naming rules, an agent has enough to call it correctly; only truncation/paging behavior at the row cap is unaddressed.

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?

With 100% schema coverage the baseline is 3, and the description genuinely adds semantics beyond the schema: how extra_paths entries map to table names (filename stem, e.g. lb.sas7bdat -> lb) and how name conflicts resolve. The remaining parameters (limit, offset, apply_labels) are left entirely to the schema.

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?

Names a specific verb (execute DuckDB SQL) and resource (dataset), pins the main table name as `dataset`, and restricts the dialect to SELECT/WITH. That level of specificity cleanly separates it from read_dataset, summarize_dataset, and frequency.

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?

Explicitly states the intended scenario — cross-dataset comparison via extra_paths — and backs it with a concrete FULL JOIN example. It stops short of saying when to prefer the simpler siblings (read_dataset/summarize_dataset) instead, so it is clear context without exclusions.

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