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DocImprint Document Intelligence

Official

Extract Text from URL

url.extract
Read-only

Extract raw text and metadata from any public HTTPS URL. Get page title, word count, and content from online articles and documents.

Instructions

Fetch a public HTTPS URL and return extracted text and page metadata. Lean mode — no evidence bundle stored, no bundle_id returned. Use for raw text extraction from web pages and online documents. Use url.summarize for summaries, url.qa for Q&A, url.translate for translation, document.extract_text for base64 file uploads. Returns: { url, title, word_count, text, final_url (after redirects) } Example prompts:

  • "Extract the text from https://example.com/report.pdf for me."

  • "Get me the raw content of this web page: [URL]."

  • "Pull the text from this online article so I can analyze it."

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic HTTPS URL to fetch and extract. Example: "https://example.com/report.pdf" or "https://blog.example.com/article"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
textYes
titleNo
final_urlNo
word_countNo
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds behavioral nuance: lean mode, no evidence bundle stored, no bundle_id returned, and final_url after redirects. It also restricts to public HTTPS URLs, which is useful context beyond 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.

Conciseness5/5

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

The description is front-loaded with the core function, then provides alternatives, return structure, and example prompts. It is well-structured, with each section earning its place and no redundant filler.

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

Completeness5/5

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

For a simple single-parameter read-only tool, the description covers purpose, usage boundaries, return format, and example prompts. With output schema and annotations present, nothing critical is missing.

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

Parameters3/5

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

Schema covers the single url parameter with a description and example (100% coverage). The description reinforces the HTTPS requirement and provides example prompts, but adds little else beyond what the schema already provides.

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

Purpose5/5

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

The description clearly states the verb+resource: 'Fetch a public HTTPS URL and return extracted text and page metadata.' It distinguishes from sibling tools by naming alternatives for summaries, Q&A, translation, and file uploads, making the tool's unique role explicit.

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

Usage Guidelines5/5

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

Explicitly directs when to use this tool vs alternatives: 'Use url.summarize for summaries, url.qa for Q&A, url.translate for translation, document.extract_text for base64 file uploads.' It also notes the lean mode with no bundle storage, implying a lightweight use case.

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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