Raw Query

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it does so thoroughly. It states that only read-only single-statement SELECT/WITH queries are allowed, results are capped at row_limit rows, and the tool returns raw table rows rather than curated responses, bypassing the caveats of the curated tools.

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 dense but well-organized, leading with the use case, then the operational constraints, then the guidance to prefer alternatives. Every sentence earns its place and there is no redundant restatement of the tool name or schema fields.

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 tool's complexity, the description covers purpose, usage, constraints, parameter semantics, and relationship to siblings. The presence of an output schema means return-value documentation is already handled structurally, so nothing essential is missing for an agent to select and invoke the tool correctly.

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 description coverage is 0%, so the description must compensate, and it does. It explains that `series` is aliased to the source Parquet identified by `series_id`, that `sql` must be a read-only SELECT/WITH statement, and that `row_limit` caps the returned rows. These meanings are not present in the bare input 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?

The description clearly identifies the tool as an escape hatch for shapes curated tools don't cover, specifies the resource (raw Parquet source behind `series`), and the operation (read-only SELECT/WITH). It also explicitly contrasts itself with get_series, which returns only curated registry-filtered rows, making sibling differentiation unambiguous.

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 gives an explicit usage rule: prefer get_series/compare_series/compute when they cover the question, and use raw_query only when they don't. It also provides a concrete example scenario (division/sector/group breakdown) and states the constraints under which the tool can be used.

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