Agent Toolbox

Extract Free

extract_free

Read-onlyIdempotent

Free. Extract structured JSON from a web page or text with a checked quote per field (up to 8 fields, Qwen3), 20 a day per IP. extract_data is the paid version: gpt-oss-120b, up to 25 fields, no limit.

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": {
      "fields": "<fields>"
    },
    "name": "extract_free"
  }
}

Input Schema

Name	Required	Description
`url`	No	A public http(s) URL
`text`	No	Text to read instead of a URL (up to 60,000 characters)
`fields`	Yes	Field name -> "type: what it is" (types: string, number, integer, boolean), e.g. {"price": "number: the current price"}; a JSON Schema with properties also works
`render`	No	Open the page in a real headless Chrome first, for pages built with JavaScript (slower; default false)

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 28, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive), and the description adds genuinely non-schema behavior: the 20-per-day-per-IP quota, the model used, and the checked-quote-per-field guarantee. It doesn't say what happens when the quota is exhausted (error vs queue) or how partial results behave, which is the remaining gap.

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 sentences, zero filler, with the tier label and the core verb front-loaded before the sibling comparison. Nothing repeats structured data verbatim.

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

Completeness4/5

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

Return shape is described qualitatively (structured JSON with a checked quote per field), which partly compensates for the absent output schema, and the quota covers the main operational risk. Without an output schema, more detail on the exact response envelope or failure modes would be needed for a 5.

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 a constraint not encoded anywhere in the schema: a maximum of 8 fields. That is real added meaning for the only required parameter's contents. It adds nothing beyond the schema for url, text, or render.

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

Purpose5/5

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

States a specific verb and resource ('Extract structured JSON from a web page or text'), plus the defining behavioral trait of a verified quote per field. It also names the sibling extract_data and what differentiates it, so an agent can distinguish the two without opening either schema.

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?

Explicitly frames this as the free tier (8 fields, Qwen3, 20/day per IP) and contrasts extract_data as the paid option with 25 fields and no limit, which is enough for an agent to route between them. What's missing is an explicit 'use this when… use the other when…' trigger, so the routing is inferable rather than stated.

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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