Extract tables from a PDF

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the detection mechanism (PDF drawing operations and text alignment, not OCR/model guesswork) and clarifies the output is limited to tables. This adds meaningful context beyond a simple 'extract tables' statement, though it does not discuss error handling or performance limitations.

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 three focused sentences: the first states the core action, the second gives a use case, and the third explains the underlying method. Each sentence serves a distinct purpose, and there is no redundant information or filler.

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 tool with three parameters and no output schema, the description provides a complete picture: what it returns, how it works, and when to use it. The Markdown output format is clearly stated, and the method explanation (drawing operations/text alignment) addresses common concerns about accuracy.

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 schema already provides 100% coverage for all three parameters, including descriptions for path, pages, and maxChars. The tool description does not add additional parameter-level detail, so it meets the baseline for schema-covered parameters without adding extra semantic value.

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 uses a specific verb ('Return only the tables') and clearly identifies both the resource (local PDF) and the output format (Markdown). It explicitly differentiates itself from sibling tools by emphasizing it skips prose and focuses on tables, which pdf_extract, pdf_search, and pdf_classify do not.

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 states when to use this tool ('Useful for invoices, financial statements and reports where the numbers are the point'). It implies a clear use case for table-focused extraction, but does not explicitly mention when not to use it or name alternative tools for non-table extraction scenarios.

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