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scrape_website

Extract clean, readable text from any website by removing ads and clutter, with optional deep scanning of contact and about pages to find contact information.

Instructions

Acessa um site, remove lixo/anúncios e extrai o texto legível e subpáginas de contato.

Args: url: URL completa do site (ex: https://empresa.com.br). deep_contacts: Se True, vasculha também páginas internas como /contato e /sobre.

Returns: Texto limpo e estruturado extraído da página.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
deep_contactsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses meaningful behavior: it cleans the page, extracts readable text, and optionally crawls internal pages such as /contato and /sobre. However, it does not mention limitations like JavaScript-rendered pages, potential blocking, rate limits, or the exact meaning of 'subpáginas de contato'.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is concise and well-organized with Args and Returns sections. The phrase 'subpáginas de contato' is slightly awkward and could be clearer, but overall it is efficient and front-loaded with the core purpose.

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?

The description covers the key parameters and return type well for a two-parameter tool, and the presence of an output schema reduces the need to describe return values. However, it lacks guidance on when to use the tool versus siblings, and the contact-subpage behavior is ambiguous enough that an agent may not know exactly what will be returned.

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

Parameters5/5

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

Schema description coverage is 0%, so the description fully compensates by explaining both parameters. It gives an example URL format and clearly defines the deep_contacts behavior, including which kind of internal pages are scanned.

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 accesses a website, removes ads/junk, and extracts readable text and contact subpages. It distinguishes the tool from contact-only extraction by emphasizing the text-scraping behavior, but it does not explicitly contrast it with siblings like extract_contacts.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives such as extract_contacts or hunt_company. It explains what the tool does but never states when it should be preferred, when it should not be used, or which sibling covers other cases.

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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