query_data

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

With no annotations, the description carries the full behavioral burden. It clearly states the operation is read-only, limits each call to one SELECT statement, reveals join-key incompatibilities, and warns about the owned/delivered row-set and generation/purchased-power mixing traps. These are meaningful behavioral disclosures beyond a generic 'run a query.'

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?

Although long, the description is tightly organized: purpose, prerequisite, constraints, join-key reference, known traps, and an example. No sentence is wasted; the density is justified by the complexity of the database schema.

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 complex multi-table schema and existing output schema, the description is remarkably complete. It identifies all relevant tables, join keys, the table that lacks an ID, and both data-quality traps. It also delegates table/column discovery to list_tables() rather than trying to inline the full schema.

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 0% and the only parameter is an undocumented 'sql' string. The description fully compensates by defining acceptable syntax, query structure, join constraints, required filters, and providing a concrete example. An agent can confidently construct a correct SQL value from this guidance.

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 opens with a specific verb and resource: 'Run a read-only SQL query against the database.' It also clarifies the SQL dialect (DuckDB), immediately distinguishing this general-purpose query tool from the specialized sibling get_* and table-inspection tools.

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 strong usage guidance: call list_tables() first, one SELECT per call, CTEs allowed, join-key mapping per table, and filter traps to avoid double-counting. It does not explicitly compare this tool to specialized siblings like get_emissions_trend, so the 'when vs alternatives' guidance is slightly implicit rather than stated.

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