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ekas-io

open-sales-stack

by ekas-io

website_intel_extract

Extract structured data from webpages as JSON by providing a custom schema and natural-language prompt. Supports single-page scraping with JS rendering or multi-page crawling of internal links.

Instructions

Scrape or crawl a webpage and extract structured data as JSON using a custom schema. Use this tool when you know the specific URL of a website and need to extract particular information in a well-defined, structured format.

Two modes are available: • 'scrape' (default) — single-page extraction with full JS rendering. • 'crawl' — multi-page extraction that follows links up to a page limit.

You MUST provide three things:

  1. The target URL

  2. A JSON Schema object defining the exact shape of the data you want returned

  3. A natural-language prompt describing what to extract

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull URL of the page to scrape or the starting page to crawl. Must include `http://` or `https://`. Example: `https://stripe.com/about`; `https://company.com/pricing`
modeNoExtraction mode. `"scrape"` renders and extracts a single page. `"crawl"` follows internal links from the starting URL up to `limit` pages, useful for discovering content across a site section. Example: `scrape`; `crawl`scrape
limitNoMaximum number of pages to visit when `mode` is `"crawl"`. Clamped to 1–10. Ignored in `"scrape"` mode. Example: `5`
promptYesNatural-language instruction telling the LLM what information to extract from the page and how to populate the schema fields. Example: `Extract the company name, the year it was founded, and the number of employees listed on this about page.`
schemaYesJSON Schema object defining the exact structure of data to extract. Use standard JSON Schema types (string, number, boolean, array, object). Each property should have a type and description. Example: `{"type": "object", "properties": {"company_name": {"type": "string"}, "founded_year": {"type": "number"}, "employee_count": {"type": "string"}}}`

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description must fully disclose behavior. It explains the two modes ('scrape' with JS rendering, 'crawl' with page limit), the requirement for a schema and prompt, and the return format (structured JSON). It does not mention rate limits, authentication, or side effects, but for a read operation like scraping, these gaps are minor. The description is sufficient for an agent to understand what the tool does and its boundaries.

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 highly concise yet comprehensive. It uses a bullet-like structure for modes and requirements, making it easy to parse. Each sentence serves a purpose: stating the tool's function, usage context, modes, and mandatory inputs. There is no fluff or redundancy. It is well-organized and front-loaded with the core action and requirements.

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 tool's complexity (5 parameters, modes, nested schema) and the presence of an output schema (which reduces the need to explain return values), the description is complete. It covers all aspects: what the tool does, when to use it, the two modes, the three required inputs, and examples for each parameter. The agent has all the information needed to invoke the tool correctly without ambiguity.

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 description coverage is 100%, meaning every parameter has a description in the schema. The description adds value by explaining the modes, the necessity of three things, and providing clear examples for each parameter. For instance, it clarifies the difference between 'scrape' and 'crawl' and gives use-case examples for the prompt and schema. This extra context goes beyond the schema, justifying a score above the baseline of 3.

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 tool's purpose: 'Scrape or crawl a webpage and extract structured data as JSON using a custom schema.' It provides specific verbs (scrape/crawl) and the resource (webpage), making it unambiguous. With no sibling tools to differentiate, it achieves maximum clarity.

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 specifies when to use the tool: 'when you know the specific URL of a website and need to extract particular information in a well-defined, structured format.' It also outlines two modes and the three required inputs. Although it does not explicitly state when not to use it or compare to alternatives, the context is clear enough for an agent to decide. The lack of sibling tools reduces the need for exclusions, so a 4 is appropriate.

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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