list_tables

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

The description suggests a benign, read-only listing operation, but annotations indicate destructiveHint=true and readOnlyHint=false, creating a direct contradiction. The description does not explain this destructive potential or any other behavioral traits like authentication needs or rate limits. Annotation contradiction detected.

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 a single, concise sentence that effectively communicates the tool's purpose without any redundancy or unnecessary information.

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?

Despite the tool's simplicity, the description lacks important contextual details such as what 'column counts' means, the behavior for invalid source names, or the output format. The contradictory annotations further reduce completeness, as the description does not reconcile them.

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?

Schema coverage is 100% with a clear parameter description for 'source_name'. The tool description does not add any additional meaning beyond the schema, so the baseline of 3 applies.

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 action ('Lists all available tables') and the resource ('in a database source'), and specifies the output includes 'column counts'. This distinguishes it from sibling tools like describe_table (which likely provides detailed table schema) and query_database (which executes arbitrary queries).

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?

No explicit guidance on when to use this tool versus alternatives such as describe_table or query_database. The use case is implied for getting an overview of tables, but no 'when-not-to-use' or alternative recommendations are provided.

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