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extract

Automatically extracts structured data from web pages by trying multiple strategies (JSON-LD, metadata, scripts, etc.) and returning the highest-confidence result. Let the tool decide the best extraction method.

Instructions

Auto-strategy structured-data extraction. Tries JSON-LD (schema.org) → NEXT_DATA → Nuxt → JSON-in-script (Magento, Shopify, BigCommerce custom-typed scripts) → OpenGraph/meta → microdata → text_main fallback, returns the highest-confidence hit as {strategy, confidence, data, tried}. Use this as the one-shot 'give me the data, you figure out how' call when you don't want to plan the strategy yourself. Pass strategy='json_ld' (or any of the names above) to force a specific extractor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
strategyNoOptional: force a specific extractor (json_ld, next_data, nuxt_data, json_in_script, og_meta, microdata, text_main)
Behavior5/5

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

Describes the full extraction strategy fallback order, the return format ({strategy, confidence, data, tried}), and the behavior when a specific strategy is forced. No annotations provided, but the description covers all behavioral aspects.

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: first explains the algorithm and return, second explains usage and parameter override. No wasted words, front-loaded with key information.

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?

Despite no output schema, the description fully explains the return structure and behavior. Covers algorithm, usage, and parameter control. Complete for a tool with one optional parameter.

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

Parameters5/5

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

The only parameter 'strategy' is described in schema with a brief description. The tool description adds value by listing all possible values and explaining the effect of passing a specific strategy (force extractor).

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?

The description clearly states the tool's purpose: 'Auto-strategy structured-data extraction' with a specific fallback order. It distinguishes from sibling tools like extract_cards, extract_list, extract_table by being a generic one-shot extractor.

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?

Explicitly tells when to use ('one-shot...when you don't want to plan the strategy yourself') and how to force a specific strategy. No alternative tools mentioned but provides clear usage context.

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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