List Tables

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that the tool returns basic table info WITHOUT column details, with empty columns lists and is_summary_table not set, and explains the performance rationale. There is no contradiction between description and 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 concise, well-structured with a lead sentence, bullet points, and an important note. It front-loads the purpose and uses efficient language without redundancy. 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 complexity, existence of output schema, and annotations, the description is complete. It explains what the tool returns and what it deliberately omits (column details, is_summary_table), and provides guidance on next steps (get_table_info). This suffices for an agent to understand and invoke the tool 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?

Schema description coverage is 0%, so the description needs to compensate. It explains the 'database' parameter and that 'like' and 'not_like' are for pattern filtering. However, it does not specify the exact pattern format (e.g., SQL LIKE syntax), which would be helpful. Overall, it adds meaning beyond the schema but could be slightly more precise.

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 it lists tables in a database for exploration and discovery. It specifies the verb 'list', the resource 'tables', and the context 'in a database'. It differentiates from siblings by noting it is lightweight and that column details are intentionally omitted, with a reference to get_table_info for more detail.

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 says when to use the tool: to discover tables, filter by name pattern, and get basic metadata. It gives an 'IMPORTANT' instruction to call get_table_info before querying a specific table, and explains that this tool is intentionally lightweight to avoid loading schema, thus guiding the agent to alternative tools when needed.

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