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veroq_crawl

Extract structured content and analyze link structures from webpages by crawling URLs with configurable depth and page limits.

Instructions

Crawl a URL and extract structured content with optional link following.

WHEN TO USE: When you need to extract and analyze content from a specific webpage, or crawl a site's link structure. RETURNS: Page content, metadata, and discovered links per page crawled. COST: 3 credits. EXAMPLE: { "url": "https://sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=AAPL", "depth": 1 } CONSTRAINTS: Max depth 3, max 10 pages per crawl.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to crawl and extract content from
depthNoCrawl depth (default 1)
max_pagesNoMax pages to crawl (default 5)
include_linksNoInclude extracted links in response
Behavior5/5

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

With no annotations provided, the description carries full disclosure burden and excels by specifying COST ('3 credits'), operational CONSTRAINTS ('Max depth 3, max 10 pages'), and RETURN format ('Page content, metadata, and discovered links'). This provides critical behavioral context beyond the input 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?

Excellent structured formatting with clear section headers (WHEN TO USE, RETURNS, COST, EXAMPLE, CONSTRAINTS). Information is front-loaded with the core purpose, and every line delivers distinct operational metadata without redundancy.

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?

Given the absence of annotations and output schema, the description comprehensively covers operational constraints, credit costs, and return value structure. The constraints section clarifies tool limits (depth 3, 10 pages) that would otherwise be unknown, making it complete for safe invocation.

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?

Schema coverage is 100%, establishing a baseline of 3. The description adds value through the EXAMPLE block, which demonstrates parameter usage patterns and JSON structure, helping agents understand how to construct valid inputs beyond the raw schema definitions.

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 opening sentence clearly states the core action ('Crawl a URL and extract structured content') and key feature ('optional link following'), providing specific verbs and resources. However, it does not explicitly distinguish from siblings like `veroq_extract` or `veroq_web_search` that may 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 Guidelines4/5

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

The 'WHEN TO USE' section provides explicit guidance on scenarios ('extract and analyze content from a specific webpage, or crawl a site's link structure'). It lacks explicit naming of alternative tools to use instead, but the context is clear enough for selection.

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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