list_tables

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

With no annotations provided, the description carries the burden of disclosing behavior. It communicates that the tool only lists tables and descriptions, and it states the nature of the output. This is sufficiently transparent for a read-only discovery tool, though it doesn't mention potential permissions or data volume considerations.

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?

Two concise sentences: the first states the action and output content, and the second provides usage direction. No wasted words, and the key functionality is front-loaded.

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 zero-parameter, no-output-schema tool, the description is fully sufficient. It tells the agent what it returns (table names, descriptions, row counts) and why to call it first. No critical missing information affects correct invocation.

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?

The tool has zero parameters, so parameter semantics are trivial. The description adds appropriate context about what the returned list represents, fulfilling the baseline guidance for a no-parameter tool.

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 states the verb 'List', the resource 'tables in the shop database', and specifies the output content (short description and row count). It distinguishes itself from the sibling query/specific-report tools by serving as a discovery entry point.

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?

Explicitly tells the agent to use this tool first before writing queries or calling other tools, giving clear when-to-use guidance. It does not name specific alternative tools or state when not to use it, but the instruction to use it before others is strong.

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