list_schemas

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

Annotations already indicate read-only and non-destructive behavior. The description adds value by noting the output includes owner and table count, and that the database parameter defaults to the session database, which are useful behavioral details beyond the annotations.

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 with an Args section. It is front-loaded with the purpose and avoids unnecessary verbosity; every word contributes to understanding.

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 simple nature of the tool, the presence of an output schema, and annotations covering safety, the description provides all necessary information. It explains the single parameter and what the tool returns, making it complete.

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 sole parameter 'database' is fully explained in the description, including its default behavior. Since schema description coverage is 0%, the description carries the full burden and does so effectively.

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 schemas in a PostgreSQL database, including owner and table count. This distinguishes it from siblings like list_tables and list_databases by specifying the resource (schemas) and output details.

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 implies usage when schema-level information is needed, but it does not explicitly contrast with alternatives or provide when-not-to-use conditions. Sibling tools are present but no direct comparison is given, so guidance is only implicit.

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