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acchuang

Jina AI Remote MCP Server

by acchuang

parallel_read_url

Extract clean content from multiple web pages simultaneously to compare information across sources or gather data efficiently.

Instructions

Read multiple web pages in parallel to extract clean content efficiently. For best results, provide multiple URLs that you need to extract simultaneously. This is useful for comparing content across multiple sources or gathering information from multiple pages at once.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesArray of URL configurations to read in parallel (maximum 5 URLs for optimal performance)
timeoutNoTimeout in milliseconds for all URL reads
Behavior3/5

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

With no annotations provided, the description carries the full burden. It mentions 'efficiently' and 'for best results... maximum 5 URLs for optimal performance' (implied rate/performance limits), but doesn't disclose error handling, authentication needs, or what 'clean content' specifically means. It adds some behavioral context but leaves gaps.

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 appropriately sized with three concise sentences. The first states the purpose, the second gives usage guidance, and the third provides context—all front-loaded with zero wasted words.

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?

Given no annotations and no output schema, the description is moderately complete for a tool with 2 parameters and 100% schema coverage. It covers purpose and usage but lacks details on output format, error cases, or deeper behavioral traits, leaving room for improvement.

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 adds minimal parameter semantics beyond the schema—it emphasizes 'multiple URLs' and 'simultaneously' for the 'urls' parameter but doesn't explain 'timeout' or the nested options ('withAllLinks', 'withAllImages').

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 specific action ('read multiple web pages in parallel to extract clean content efficiently'), identifies the resource ('web pages'), and distinguishes it from sibling tools like 'read_url' by emphasizing parallel processing and multi-URL capability.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool ('for comparing content across multiple sources or gathering information from multiple pages at once') and mentions 'for best results, provide multiple URLs.' However, it doesn't explicitly state when NOT to use it or name alternatives like 'read_url' for single URLs.

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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