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Run read-only SQL SELECTs against the shop database to explore and join data for questions analytics tools don't cover. Use limit and offset to paginate results.

Instructions

Run a read-only SQL SELECT query against the shop database. Use this for any question not directly covered by the specialized analytics tools, or to explore/join data freely once you know the schema. Only a single SELECT (or WITH ... SELECT) statement is allowed — write operations and multiple statements are rejected. Results are capped at limit rows; use offset to page through more.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYes
limitNo
offsetNo
Behavior5/5

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 well: it states the operation is read-only, only single SELECT or WITH...SELECT statements are accepted, write operations and multiple statements are rejected, and results are capped with pagination support. No major behavioral surprise remains.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, front-loaded with the core purpose, and each sentence adds meaningful guidance. No fluff or repeated schema information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an open-ended SQL query tool, this is complete: it identifies what tool does, what queries are permitted, what happens on violation, and how to handle large result sets. There is no output schema to document, and the sibling tools supply the schema-discovery path.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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. It clarifies that sql must be a SELECT-style query, that a session limit caps returned rows, and that offset pages through additional results. It does not spell out defaults or maximums, but those constraints are already visible in the JSON schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

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 SELECT query against the shop database.' It also distinguishes itself from the specialized analytics tools by positioning itself as the general-purpose query tool for questions those tools do not directly cover.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear when-to-use guidance: use it for anything not covered by specialized analytics tools and for free exploration/joins once the schema is known. It stops short of explicitly naming siblings like list_tables or get_revenue_report, but the exclusion of 'specialized analytics tools' is sufficient guidance.

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

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