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URL Extract

url_extract
Read-onlyIdempotent

Extract normalized main text and optional links from any public HTTP/HTTPS URL. Returns title, author, publication time, language, and content hash.

Instructions

Extract normalized main text and optional links from a public HTTP or HTTPS document. Returns title, author, publication time, language, content hash, truncation and cache state. Output size and fetch time are bounded; JavaScript is not executed. Pass url as an absolute public HTTP(S) URL. Set include_links=true only when normalized links are needed. Keep fresh=false to reuse cache.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesAbsolute public HTTP or HTTPS URL to inspect. Private, loopback, link-local, metadata-service and otherwise SSRF-sensitive destinations are rejected.
freshNoSet true only when a new upstream fetch is required; false allows the bounded cached result and is cheaper for the origin.
include_linksNoSet true to include bounded normalized links in extraction output; false returns the main document text without the optional link list.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
linksYes
titleYes
authorYes
qualityNo
languageYes
truncatedYes
url_finalYes
checked_atYes
from_cacheYes
request_idYes
text_lengthYes
content_hashYes
published_atYes
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive. The description adds valuable context: bounded output size and fetch time, no JavaScript execution, and cache reuse behavior, enhancing transparency beyond annotations.

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?

Three sentences: first clearly states purpose and outputs, second gives parameter guidance, third addresses caching. Every sentence is essential and front-loaded with key information.

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

Completeness4/5

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

Given output schema exists and annotations cover safety, the description covers constraints (public URL, bounded output), usage hints, and cache behavior. It could mention error handling or retry behavior, but overall sufficient for a simple extraction tool.

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

Parameters4/5

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

All parameters have schema descriptions (100% coverage). The description adds extra meaning: url must be absolute public HTTP(S), include_links only when needed, and fresh=false for cache, which aids correct usage.

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?

The description clearly states the tool extracts normalized main text and optional links from public HTTP(S) documents, listing return fields. However, it does not explicitly distinguish from sibling tools like url_text or url_links, which overlap in functionality.

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

Usage Guidelines3/5

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

Provides parameter usage tips: require absolute public URL, recommendation to set include_links only when needed, and use fresh=false for cache reuse. But it lacks guidance on when to choose this tool over related sibling tools.

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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