list_tables

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

With no annotations, the description fully discloses the return format (JSON-encoded string with tables, next_page_token, total_tables) and explains the effect of include_detailed_columns on payload size. It does not mention auth or rate limits, but as a read-only operation, this is acceptable.

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 well-structured with an introductory sentence, Args section, and Returns section. Every sentence adds value, and there is no redundancy or fluff. It is appropriately sized for the tool's complexity.

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 presence of an output schema, the description adequately covers behavior and options. It could mention edge cases (e.g., empty database or table names with special characters), but overall it provides sufficient information for an agent to use 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 must explain each parameter. It does so comprehensively, including defaults (page_size=50, include_detailed_columns=True) and behavior (e.g., include_detailed_columns=False empties columns array but keeps create_table_query).

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 verb 'list' and the resource 'ClickHouse tables in a database', including specific details like schema, comment, row count, and column count. This distinguishes it from sibling tools 'list_databases' and 'run_query'.

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 clear context for using optional filters (like, not_like), pagination (page_token, page_size), and performance optimization (include_detailed_columns). It does not explicitly state when not to use the tool or provide direct comparisons to siblings, but the differentiation is implicit.

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