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crw_crawl

Crawl websites to extract structured data using JSON schemas. Start with a URL, set depth and page limits, then monitor progress with job IDs.

Instructions

Start an async crawl of a website. Returns a job ID that can be polled with crw_check_crawl_status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jsonSchemaNoJSON schema for LLM-based structured data extraction on each crawled page
maxDepthNoMaximum crawl depth (default: 2)
maxPagesNoMaximum number of pages to crawl (default: 10)
urlYesThe starting URL to crawl
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 discloses that the crawl is async and returns a job ID for polling, which is useful behavioral context. However, it lacks details on permissions, rate limits, error handling, or what the crawl actually does beyond extraction (e.g., storage, format).

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 two sentences, front-loaded with the main purpose and followed by essential usage guidance. Every word earns its place with no redundancy or fluff, making it highly efficient and easy to parse.

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, no output schema, and a tool that starts an async process with 4 parameters, the description is adequate but incomplete. It covers the purpose and basic workflow but lacks details on output (beyond job ID), error cases, or behavioral constraints like timeouts or resource usage.

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 schema already documents all parameters well. The description adds no parameter-specific information beyond what the schema provides, such as explaining the interaction between maxDepth and maxPages or the format of jsonSchema. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('Start an async crawl of a website') and the resource ('a website'), distinguishing it from siblings like crw_check_crawl_status (polling), crw_map (mapping), and crw_scrape (scraping). It provides a complete picture of the tool's function.

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 explicitly states when to use this tool ('Start an async crawl') and mentions the alternative tool for polling results ('crw_check_crawl_status'), providing clear context. However, it doesn't specify when not to use it or differentiate from other siblings like crw_map or crw_scrape.

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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