Extract structured JSON from a web page (by URL) or raw HTML: title, byline, excerpt, siteName, publishedTime, language, plain text, links, images, and meta tags. Paid tool: $0.005 per call via x402 (USDC on Base).
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Public http(s) URL of the page to fetch and convert | |
| html | No | Raw HTML to convert instead of fetching a URL | |
| mode | No | article (default): main content only. full: whole page. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the tool is paid ($0.005 per call via x402) and lists output fields. It does not explicitly state it is read-only, but the output structure implies no destructive side effects.
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: the first lists key outputs, the second states pricing. It is front-loaded, concise, and every sentence adds value.
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?
With 3 parameters, no output schema, and no annotations, the description adequately covers purpose, parameters, cost, and output. It could mention pagination or error handling, but overall it is complete for a simple tool.
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?
Schema coverage is 100%, but the description adds value by summarizing the output structure (title, byline, etc.) and noting the default mode (article). This complements the schema's parameter descriptions.
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 extracts structured JSON from a web page or raw HTML, listing specific fields (title, byline, etc.). This distinguishes it from siblings like html_to_markdown (which converts to markdown) and service_info (which provides info).
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 implicitly tells when to use (when structured extraction is needed) and mentions pricing (paid tool). It does not explicitly compare with alternatives or state when not to use, but the context is clear enough.
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.
Each tool has a distinct purpose: extract_page extracts JSON metadata, html_to_markdown converts to Markdown, and service_info provides pricing details. No overlap or confusion.
All names use consistent lowercase snake_case with a verb-noun pattern: extract_page, html_to_markdown, service_info. Predictable and clear.
Three tools is well-scoped for a focused HTML-to-Markdown service. Each tool serves a necessary role without bloat or thinness.
The tool set covers the core workflows: extracting structured data, converting to Markdown, and accessing service info. No obvious gaps for the stated purpose.