extract_tables

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

With no annotations, the description carries full behavioral burden. It discloses the exact return contract (list of page, index, num_rows, num_cols, markdown, rows) and clarifies row structure. It does not address potential side effects or performance, but as a read-only extraction tool the output contract is the most relevant behavioral trait.

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 short, front-loaded with the action, and uses a compact structured list for the return shape. Every sentence adds useful information with no 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?

The tool has 2 parameters and no annotations, and the description covers the core extraction behavior and output shape. However, it omits semantics for source and ocr_languages, and does not explain when to prefer this over convert_to_markdown or convert_to_text, leaving integration gaps for the agent.

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 compensate. It implies 'source' refers to a document but does not explain accepted formats (path, ID, content). The ocr_languages parameter is completely unexplained, leaving a required part of the invocation ambiguous.

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 opens with 'Extract all tables from a document', a specific verb+resource that clearly distinguishes from sibling tools like convert_to_text or convert_to_markdown. It also specifies the produced data structure, reinforcing the tool's table-focused purpose.

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?

There is no explicit guidance on when to use this tool vs alternatives. The phrase 'Extract all tables' implies a use case (need structured table data), but it does not mention sibling conversion tools, exclusions, or preconditions such as OCR requirements.

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