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DocImprint Document Intelligence

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Ask a Question About a URL

url.qa
Read-only

Fetch a public HTTPS URL and answer a specific question about its content with cited evidence. Use for precise queries like refund policies or delivery terms.

Instructions

Fetch a public HTTPS URL and answer a specific question about its content. Lean mode — no bundle stored. Use when you have a precise question about a web page. For a broad summary, use url.summarize. For multi-document Q&A, use collection.ask instead. Returns: { url, answer, answer_cited: { value, confidence, citations[] }, confidence: "high"|"medium"|"low", truncated } Example prompts:

  • "What is the refund policy at https://docs.example.com/policy?"

  • "Look at [URL] and tell me what the delivery terms are."

  • "Answer this question based on the content of [URL]: [question]."

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic HTTPS URL to fetch and question. Example: "https://docs.example.com/policy"
questionYesSpecific question to answer from the page content. Example: "What is the refund policy?"
max_tokensNoInput length cap (1 token ≈ 4 chars). Truncates fetched page content, not the answer. Example: 4000

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
answerNo
truncatedYes
confidenceNo
answer_citedNo
Behavior4/5

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

Annotations declare readOnlyHint=true and openWorldHint=true, while the description adds behavioral details such as 'Lean mode — no bundle stored' and the 'truncated' field in the return value, indicating potential truncation. This goes beyond annotations, though it omits failure modes or rate limits, so not a 5.

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 well-structured with a clear action statement, usage guidance, return format, and example prompts. It is front-loaded with the core purpose and every sentence adds value. No wasted words.

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 straightforward fetch-and-answer tool, the description covers: what it does, when to use it, alternatives, return value structure, and example invocations. Output schema exists, but the description still explains the return fields. No significant gaps.

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 description coverage is 100%, so the baseline is 3. The description does not add parameter-level details beyond the schema, but it includes example prompts that illustrate parameter usage. The schema already explains max_tokens truncation behavior.

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 a specific verb and resource: 'Fetch a public HTTPS URL and answer a specific question about its content.' It differentiates from siblings by explicitly naming url.summarize and collection.ask as alternatives, and adds 'Lean mode — no bundle stored' to set it apart.

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?

Provides explicit usage guidance: 'Use when you have a precise question about a web page.' It also gives clear exclusions and alternatives: 'For a broad summary, use url.summarize. For multi-document Q&A, use collection.ask instead.' This is high-quality differentiation.

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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