Scrapes a webpage and returns the content in AI-readable Markdown format. Can access blocked sites through browser rendering.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL of the webpage to scrape | |
| format | No | Output format: markdown (default) or text | markdown |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description must carry the full burden. It discloses that the tool uses browser rendering to access blocked sites, which is a useful behavioral detail. However, it doesn't mention potential limitations, rate limits, or error behavior, so transparency is incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, with the primary purpose stated first and the key capability (browser rendering for blocked sites) as a secondary note. Every sentence is informative and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core function and a differentiator, but it misses the distinction from scrape_urls, which could lead to agent confusion. Since there is no output schema, the description does mention the return format sufficiently. Overall, it's adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides descriptions for both parameters (url and format), and the context signal indicates 100% schema description coverage. The tool description doesn't add significant parameter-level meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it scrapes a webpage and returns content in Markdown format, which is specific and action-oriented. However, it doesn't differentiate from the sibling tool scrape_urls, which likely handles multiple URLs, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions the ability to access blocked sites through browser rendering, which gives some context for when this tool might be preferred. However, it doesn't explicitly state when to use this tool versus alternatives like scrape_urls, so the guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
get_billing and get_usage overlap somewhat in describing plan/credit information, but their distinct focus on billing details vs. usage/credits keeps them separable. scrape_url and scrape_urls are clearly differentiated by singular vs. plural operation. scraper_server_status is entirely distinct. Overall, the tools are mostly distinct with only mild ambiguity between billing and usage.
Most tools follow a verb_noun pattern (get_billing, get_usage, scrape_url, scrape_urls), but scraper_server_status deviates as a noun phrase. This mixed convention is still readable and predictable, but not fully consistent.
With 5 tools, the server is well-scoped for a scraping API. It covers single/batch scraping, server status, billing, and usage without unnecessary bloat, making the count appropriate for its purpose.
The tool surface covers the core lifecycle of a scraping service: scraping (single and multiple), health monitoring, and account management (billing/usage). Minor gaps exist, such as lack of detail on plan management or job cancellation, but these are not critical for the primary use case.