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list_tables

Discover all tables in the business database to understand what data is available for querying. Quickly identify the full schema structure before running read-only SQL queries against the database.

Instructions

List all tables in the business database.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries some burden. 'List all tables' conveys a non-destructive read operation, which aligns with the sibling context. However, it doesn't disclose what information is returned per table (just names? schemas? row counts?), pagination limits, or whether permissions are needed. With no annotations at all, slightly more disclosure would be valuable, but the safe-read nature is reasonably conveyed.

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

Conciseness4/5

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

A single, complete sentence with zero waste. Could arguably be considered slightly under-specified, but for a zero-parameter discovery tool, this length is appropriate and front-loaded with the essential verb-resource structure.

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

Completeness4/5

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

For a tool with 0 parameters, an output schema, and a simple list-and-return purpose, the description is adequately complete. It explains the key behavior (returns all table names) and the schema and output schema handle the rest. A bit more detail on what fields are returned per table might elevate it, but as-is it's sufficient for the tool's simplicity.

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?

The tool has 0 parameters, and schema coverage is 100% (trivially, since there are no properties). The baseline for 0 parameters is 4 per the rubric. The description doesn't need to add parameter meaning since none exist, and there's no ambiguity to resolve.

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

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the action (list all tables) and resource (business database). While it doesn't explicitly distinguish from siblings, the tool names are self-explanatory enough that list_tables vs describe_table vs run_query are obviously distinct. Could note specifics about what 'all tables' includes (e.g., system tables, schemas) but the core purpose is clear.

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

Usage Guidelines3/5

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

The description implies it's the discovery entry point (list tables before describing or querying), and the sibling names naturally establish context. However, there's no explicit when-to-use guidance or mention that this is the precursor to using describe_table or run_query. The guidance is implied by the tool name and sibling set rather than stated.

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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