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extract_structured_data

Extract structured data and metadata (OG tags, canonical, author, dates) from any website using custom CSS selectors for JSON output.

Instructions

Extract page metadata (OG tags, canonical URL, author, dates) and custom CSS selector JSON schema mapping from a website.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesTarget website URL to extract content and metadata from.
modeNoCrawl mode: 'fast' (native fetch) or 'deep' (Playwright Chromium).fast
proxyNoOptional HTTP/SOCKS5 proxy URL.
schemaNoOptional key-value map of property names to CSS selectors (e.g. { title: 'h1', price: '.price' }).
cookiesNoOptional custom HTTP cookies key-value dictionary.
headersNoOptional custom HTTP request headers key-value dictionary.
max_retriesNoMaximum retry attempts (default: 3).
css_selectorNoOptional CSS selector to scope content before processing.
include_metadataNoWhether to extract Open Graph tags, canonical URL, author, and date metadata (default: true).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, but it only states what is extracted and from where. It does not disclose that this likely performs a live network fetch, any side effects, permission or rate-limit considerations, or distinctions between the 'fast' and 'deep' modes in terms of behavior.

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 a single focused sentence with no superfluous words. It leads with the main action and resources, making it efficient and easy to parse.

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

Completeness2/5

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

For a tool with 9 parameters, nested objects, no output schema, and sibling tools to disambiguate, this one-sentence description is insufficiently complete. It omits usage guuidelines, behavioral expectations, and return-value structure, leaving meaningful gaps for an agent trying to invoke it correctly.

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?

The input schema covers all 9 parameters with detailed descriptions, including examples, so the baseline is 3. The description adds little beyond the schema: it lists example metadata fields (OG tags, canonical URL, author, dates) which clarifies output scope, but does not elaborate on parameter syntax or interplay.

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 a specific verb ('Extract') and resources ('page metadata', 'custom CSS selector JSON schema mapping'), making the tool's purpose understandable. It does not explicitly differentiate from sibling tools like extract_web_content or batch_extract_web_content, so it misses the top tier by a narrow margin.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus the sibling tools extract_web_content or batch_extract_web_content. The description does not mention any conditions, alternatives, or exclusions, leaving the agent to infer usage entirely from names.

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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