list_tables

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

The readOnlyHint annotation already establishes a safe read operation. The description adds valuable behavioral context beyond that: the tool returns metadata for all tables in the current workspace, scoped to a 'numeric tables' inventory, and includes the specific fields returned. This is adequate for a simple listing tool.

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 sentences with no filler: the first states the resource and output fields, the second provides the usage trigger. Every sentence earns its place and the key scoping information (workspace, table metadata) is front-loaded.

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 metadata-listing tool with one optional parameter and no output schema, the description is complete: it names what is listed, the fields returned, and when to invoke it. No further return-format or pagination details are necessary for correct invocation.

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 single 'module' parameter has 100% schema description coverage, listing valid filter values, so the schema does the heavy lifting. The description adds no additional parameter-level detail beyond implying the table list can be scoped by module, which keeps this at the baseline score.

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 states a specific verb ('列出' / list) and resource ('当前工作区的全部数值表') and enumerates the output fields (table name, module, row count, column names). It also positions the tool as a discovery step before querying, which separates it from read_table and other table-manipulation siblings.

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 gives explicit when-to-use guidance: use it before answering numeric questions to locate the relevant table and available columns. It does not name alternatives or state when not to use it, but the trigger context is clear enough for an agent to choose this tool over read_table or export_table.

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