export_query

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

With no annotations provided, the description carries the behavioral disclosure burden. It discloses key behaviors: streaming results directly to disk, zero token consumption, and constant memory usage. It stops short of stating file-overwrite behavior, but the core side effect and performance traits are transparent.

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 a single efficient sentence that front-loads the core action and result, then adds the most distinctive benefits (zero token consumption, O(1) memory) without filler.

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?

For a tool with a fully documented schema and an output schema, the description is largely complete: it explains what happens, where output goes, and why it is useful. It could more explicitly contrast with the query sibling or mention overwrite behavior, but those are minor omissions rather than blockers.

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 100%, so the parameters are already well-documented. The description reinforces the CSV/JSONL file destination and SQL execution, but adds little semantic value beyond what the schema provides.

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 uses a specific verb ('Execute') and resource ('SQL query') and clearly states the outcome: streaming results to a local CSV or JSONL file. This makes it easy to distinguish from sibling tools like query, which would return results in-context rather than writing to disk.

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 clear context for when to use this tool: 'ideal for large query exports' and highlights zero token consumption and O(1) memory usage. It does not explicitly name alternatives or state when-not-to-use, but the use case is clear enough to guide selection.

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