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by io.github.virgen101
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extract

Extract structured data from a web page using a JSON schema. AI-powered extraction. Cost: 0.01 USDC

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>",
      "schema": "<schema>"
    },
    "name": "extract"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesThe web page URL to extract from
intentNoNatural language description of what to extract
schemaYesJSON schema string defining the data structure to extract

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral burden. It mentions 'AI-powered extraction' and a cost of 0.01 USDC, but it does not disclose whether the operation is read-only, the output format, potential failure modes, or any rate limits. This is a significant gap for a tool with no annotation support.

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 one short sentence followed by a cost note. It is front-loaded with the verb 'Extract' and a specific resource, and every word earns its place without redundancy. This is exemplary conciseness.

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?

With no output schema and no annotations, the description is expected to explain return behavior and additional context. It covers the core purpose but omits details about the output format, the optional 'intent' parameter, and error handling. It is minimally viable but has clear gaps.

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, setting a baseline of 3. The description adds some connecting context by mentioning 'JSON schema' and 'AI-powered' (relating to the intent parameter), but it does not meaningfully enhance understanding of parameter formats or syntax beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool extracts structured data from a web page using a JSON schema, providing a specific verb, resource, and mechanism. However, it does not explicitly distinguish itself from sibling tools like crawl or fetch_page, 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.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when you need structured data from a web page with a defined schema, but it gives no explicit guidance on when to use this tool versus alternatives. There are no stated exclusions or references to sibling tools, so the guidance is only implicit.

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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