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by io.github.groundtruthtools
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Pull structured data from a page

extract_page
Read-onlyIdempotent

Read a web page and return the named fields as JSON, using only what the page states; a value the page does not give comes back empty rather than guessed. Name fields, or pass a JSON Schema, or neither for a title, summary and key points. Needs an API key (5 calls from its balance); a failed extraction is refunded.

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>"
    },
    "name": "extract_page"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesFull address, starting http:// or https://.
fieldsNoField names to fill, e.g. ['price', 'founded', 'ceo']. Letters, digits and underscores.
schemaNoA JSON Schema with type 'object', instead of fields.
instructionsNoOptional guidance, up to 500 characters.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, openWorld), yet the description adds genuinely new behavior: strict grounding ("only what the page states", missing values returned empty rather than guessed), an API-key requirement, a concrete cost of 5 calls, and refunds on failed extractions. That is exactly the cost/auth/failure context annotations cannot express.

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?

Two dense sentences with no filler: the grounding rule and default output come first, then the calling modes, then auth/cost/refund. Every clause carries information an agent needs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, output shape, default behavior, authentication, pricing, and failure handling for a 4-parameter tool with no output schema. An agent has everything needed to decide to call it and to predict the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds the important semantic that fields, schema, and neither are alternative modes with a defined default (title, summary, key points). It does not clarify interaction between instructions and the other two modes, so it stops at 4.

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?

Specific verb (read a web page) plus a precise output contract (named fields as JSON), which implicitly separates it from the raw-page sibling read_page. However, it never names read_page or any sibling explicitly, so differentiation is left to inference.

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?

"Name fields, or pass a JSON Schema, or neither for a title, summary and key points" gives clear mode-selection guidance for the three ways to call it. It stops short of saying when to prefer this over read_page or the other extraction siblings.

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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