Список таблиц базы

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

While annotations already declare the operation read-only, idempotent, and non-destructive, the description adds crucial behavioral context: the row count is an estimate from InnoDB statistics and may differ significantly from reality. This is an important caveat beyond what annotations express and helps set expectations for the returned data.

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 two concise sentences, front-loading the core functionality and then providing the key caveat about row count estimation. It ends with a clear usage recommendation, all without redundancy or unnecessary detail. Every sentence earns its place.

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 tool has zero parameters and no output schema, the description fully explains what the tool does, what data it returns, and the reliability of that data. It also provides usage guidance, making it complete for an agent to understand when and how to use it correctly.

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 the schema describes an empty object. The description compensates by detailing exactly what data is returned (engine, encoding, comment, sizes, row count estimate), providing the semantic richness that a parameterized tool would normally get from parameter descriptions. This goes beyond the baseline for no-parameter tools.

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 a specific action (list tables and views) and identifies the returned attributes (engine, encoding, comment, sizes, row count estimate). It distinctively frames itself as the starting point for exploring an unfamiliar database, which sets it apart from sibling tools like describe_table or query.

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 explicitly advises using this tool first when encountering an unfamiliar database, and it recommends COUNT(*) via the query tool for exact row counts, thereby guiding the agent on when to use this vs an alternative. This is direct and actionable.

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