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extract_structured

Read-onlyIdempotent

Extract structured metadata from web pages: JSON-LD, OpenGraph, microdata. Retrieve fields like price, rating, author, and date for analysis.

Instructions

Pull JSON-LD, OpenGraph, Twitter cards, and microdata from a web page.

Best for:
- Product pages (price, currency, availability, brand, rating).
- Article pages (author, publish date, image, headline).
- Recipe / event / video pages where rich metadata IS the answer.
- Cases where `fetch` returns prose but you need fields.

Not recommended for:
- Just reading a page -> use `fetch`.
- PDFs / DOCX -> use `read_doc`.
- Pages that don't publish schema.org metadata (most blogs) — you'll get
  empty lists; fall back to `fetch`.

Returns:
- json: {url, json_ld:[], microdata:[], opengraph:[], rdfa:[]}. Twitter
  card meta tags are surfaced inside the `opengraph` list.
- markdown (default): a flattened key/value view with each block printed
  as a JSON code block under its syntax heading.

Common mistakes:
- Calling on every URL "just in case" — most sites have no structured
  data, and `fetch` is what you actually want.

Args:
    url: Absolute http(s) URL.
    format: "markdown" (default) or "json".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Discloses that most sites have no structured data and you'll get empty lists, advising fallback to fetch. Also explains return format. Annotations (readOnlyHint, idempotentHint, openWorldHint) are consistent with description. No contradictions.

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?

Well-structured with headings, bullet points, and sections. Each part adds value (best for, not recommended, returns, common mistakes). Front-loaded with action. No fluff.

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?

Given output schema exists, description explains return shape for both json and markdown. Differentiates from sibling tools (fetch, read_doc) and covers edge cases (empty results). Complete enough for agent to use 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?

Schema has no descriptions (0% coverage). Description explains that url must be absolute http(s) and format defaults to 'markdown' with option 'json'. Adds minimal semantics beyond schema; does not describe URL validation or error behavior. Adequate but not rich.

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?

Description clearly states what the tool does: extract JSON-LD, OpenGraph, Twitter cards, and microdata from a web page. Lists specific use cases (product, article, recipe pages) and distinguishes from siblings like fetch and read_doc.

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

Usage Guidelines5/5

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

Includes explicit 'Best for' and 'Not recommended for' sections, references alternatives (fetch, read_doc), and warns about common mistakes like calling on every URL. Provides clear when-to-use guidance.

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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