scrape_pageFetch any URL and extract clean article body, headings, meta, links, and schema signals to analyze competitor content and find content gaps.
Fetch and extract clean article body, headings, meta, links, and schema signals from a URL (headless fallback for thin SPA HTML).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| forceHeadless | No |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden and does reasonably well: it discloses the headless fallback for thin SPA HTML and signals that the body is cleaned/extracted. It doesn't cover edge behavior like redirects, errors, or output format, but for a simple read tool this is solid.
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 a single well-structured sentence that front-loads the action and resource list, then adds the key conditional behavior in parentheses. Every element earns its place with no filler.
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?
For a simple two-parameter fetch tool with no output schema, the description covers what will be extracted and the main behavioral nuance. It does not describe the exact response structure, but the listed extraction targets give an agent enough context to invoke and interpret the result correctly.
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 description coverage is 0%, so the description must compensate, but it only indirectly addresses parameters: 'URL' maps to the url field and 'headless fallback' hints at forceHeadless. The description provides no explicit explanation of when or why to set forceHeadless, leaving some burden on the agent.
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 uses specific verbs ('Fetch and extract') and names the exact resources ('article body, headings, meta, links, and schema signals') from a URL. This clearly distinguishes it from the sibling analysis tools, which operate on content rather than retrieve it.
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 implies this is the raw content extraction tool versus the analysis-oriented siblings, but it never explicitly states when to choose it over alternatives or when not to use it. The usage context is clear but left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.