word_extract_tables

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

With no annotations provided, the description must disclose behavioral traits. It only states that it extracts all tables and supports two output formats, but does not mention whether the operation is non-destructive, error handling, or limitations (e.g., only .docx files are supported, though this is in the schema).

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 two sentences, front-loaded with the core purpose, and every sentence adds value. There is no unnecessary information, making it efficiently concise.

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?

The tool is simple, and the schema covers parameters and output. However, the description lacks details on return behavior, edge cases (e.g., no tables found), and error handling, leaving some contextual gaps despite having an output schema.

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 both parameters having descriptions. The description adds minimal extra meaning beyond the schema, merely restating the output format options. Therefore, the baseline score of 3 is appropriate.

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 '提取 Word 文档中的所有表格' (Extract all tables from Word document), specifying the verb and resource. It distinguishes from sibling tools like word_extract_text (text extraction) and word_extract_images (image extraction) by focusing specifically on tables.

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 no explicit guidance on when to use this tool versus alternatives. The usage context is implied by the tool's purpose, but no when-not or alternative recommendations are given, which is a gap for an AI agent.

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