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netintel_pdf_parse

Convert PDF URLs or base64 files into clean Markdown and text with page offsets, metadata, and page citations for extracting citable content.

Instructions

Parse a PDF to text and Markdown: send a PDF url or base64 file, get clean Markdown with paragraphs rebuilt from the text layer, per-page character offsets for citing pages, metadata (title, author, dates, page count) and the page numbers…

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNo
pagesNo
max_charsNo
file_base64No

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.61

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It discloses the transformation behavior (text-layer reconstruction, per-page offsets, metadata extraction), which is genuinely useful, but never explicitly states that this is a read-only operation, nor does it mention limits, failure modes for unparsable/scanned PDFs, or rate constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded in a single colon-separated sentence, but the sentence runs long by enumerating return fields and appears truncated ('and the page numbers…'), which undercuts clarity. It is not wasteful, but the trailing enumeration is unstructured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a four-parameter tool with no annotations and no output schema, the description helpfully sketches the return shape (Markdown, offsets, metadata), which offsets the missing output schema. However, the unexplained 'pages' and 'max_chars' controls and absence of any read-only/limitation statement leave real gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% across all four parameters. The description implicitly covers 'url' and 'file_base64' via 'send a PDF url or base64 file', but 'pages' (page selection) and 'max_chars' are never mentioned, leaving half the parameters undocumented in both schema and prose.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Parse a PDF to text and Markdown') and names the two accepted input forms, so the agent knows exactly what transformation this performs. The PDF-specific scope implicitly separates it from text siblings like netintel_markdown or netintel_page_extract, but no sibling is named explicitly, keeping it short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says how to feed input ('send a PDF url or base64 file') but gives no guidance on when to choose this over alternatives such as netintel_page_extract, netintel_markdown, or netintel_extract. No prerequisites, exclusions, or routing conditions are provided.

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

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