list_tables

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

With no annotations provided, the description carries the burden, and it does a good job for a list tool: 'List all extracted tables' clearly indicates a read-only operation and defines the scope, while the return-field list sets expectations. It does not mention potential performance characteristics or edge cases, but for a simple list operation this is sufficient.

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 with no filler. The primary action and scope are front-loaded, followed by the list of returned data, making it easy for an agent to parse quickly.

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 list tool with an output schema available, the description is complete. It states exactly what is listed and what information is returned, giving an agent all it needs to decide to call the tool.

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 zero parameters, so the baseline is 4. There are no parameter details to document, and the description appropriately focuses on the operation and return values rather than nonexistent arguments.

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 has a specific verb ('List'), a clear resource ('all extracted tables in the DuckDB relational store'), and enumerates the returned fields (table names, source documents, column schemas, row counts). This clearly distinguishes it from sibling tool list_documents.

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 action and scope imply usage for discovering available tables, but the description does not explicitly compare it with alternatives like query_tables or list_documents, nor state when not to use it. There is no explicit guidance on selection among siblings, so it earns an 'implied usage' score.

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