list_tables

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

The description adds one behavioral trait: the database parameter must be a plain SQL identifier. However, it does not disclose other important behaviors like read-only nature, permission requirements, or whether only visible tables are returned. With no annotations, the description carries the full burden and partially meets it.

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 concise with two sentences, no wasted words, and the primary action is stated first. Every sentence adds value.

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's low complexity (one parameter) and the presence of an output schema, the description is nearly complete. It explains the tool's purpose and parameter constraints. A minor gap is the lack of mention of return format, but that is covered by the output schema.

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 input schema has 0% description coverage, but the description fully compensates by specifying the database parameter's format (plain SQL identifier) and providing concrete constraints (letters, digits, underscore, no quotes, dots, or spaces), adding significant meaning beyond the schema.

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 tool lists tables in a given database using a specific verb and resource, and it is easily distinguishable from sibling tools like list_databases (lists databases) and describe_table (describes a specific table).

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 provides no guidance on when to use this tool versus alternatives, such as prerequisites (e.g., need to know database name first) or exclusions (e.g., cannot list tables across databases).

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