Return every table in a PDF as structured JSON (reconstructed rows and columns) with page and bounding box for verifiable citations. Uses the semantic (hybrid) engine.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | http(s) URL of the PDF. |
Changes observed during successful MCP inspections.
Input schema / properties / url / descriptionPrevious value: -"URL http(s) del PDF."New value: +"http(s) URL of the PDF."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description should fully disclose behavioral traits. While it mentions the output format and engine type, it omits critical details such as whether it is read-only, authentication needs, rate limits, error handling (e.g., PDF with no tables), and the extent of PDF support (e.g., scanned vs. text-based).
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 extremely concise (two sentences) with the main action front-loaded. Every sentence provides essential information without waste.
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 tool's simplicity (single required parameter) and lack of output schema, the description provides adequate context about the output (structured JSON with page and bounding box). However, it does not explain error scenarios, limitations (e.g., PDF accessibility, image-based tables), or contrast with similar sibling tools, leaving gaps for an AI 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?
The input schema has high coverage (100%) and includes a description for the only parameter (url). The tool description adds no extra meaning beyond the schema, adhering to the baseline of 3.
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 tool returns every table in a PDF as structured JSON with rows, columns, page, and bounding box. It uses a specific verb ('Return') and resource ('every table in a PDF'), but does not explicitly differentiate from sibling tools like extract_pdf.
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 (e.g., extract_pdf). It does not mention when not to use it or prerequisites, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.