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commerce.product-price

Read-onlyIdempotent

Paste one public retailer product URL to get its current publisher-supplied structured price, currency, availability, seller, shipping terms, aggregate rating, variant attributes, identifiers, observation time, and evidence hashes from Schema.org JSON-LD, Schema.org microdata, or paired product meta tags; optionally compare the selected offer with a buyer-supplied maximum. Fetching proceeds only when robots.txt permits it, without JavaScript, login, cookies, or anti-bot bypass.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
maximum_priceNoOptional maximum price in expected_currency; comparison is null when the publisher reports another currency
expected_currencyNoOptional ISO 4217 currency expected by the buyer

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesStructured Live product price snapshot result
metaYes
serviceYes
versionYes
request_idYesUnique request identifier

TDQS

A4.4/5.0
Behavior5/5

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

Annotations indicate read-only, idempotent, non-destructive behavior. The description adds crucial behavioral details (robots.txt compliance, no JavaScript, no anti-bot bypass) and specifies the exact output structure, going well beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long due to listing output fields, but every sentence adds value and it is front-loaded with purpose. It is efficient with no fluff, though slightly verbose.

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?

With a rich output schema and clear annotations, the description fully explains the tool's behavior, constraints, and parameter usage, making it complete for this moderately complex web-fetching tool.

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 coverage is 67%; the description clarifies the optional comparison via 'optionally compare the selected offer with a buyer-supplied maximum' for maximum_price, but does not mention expected_currency beyond its schema description. Baseline 3 is appropriate.

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 states a specific action ('Paste one public retailer product URL to get its current publisher-supplied structured price') with a clear resource and enumerates the exact data fields returned, distinguishing it from sibling tools focused on other domains.

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?

It clearly states when the tool works ('Fetching proceeds only when robots.txt permits it') and its constraints (no JavaScript, login, etc.), implying appropriate usage contexts. It does not explicitly name alternative tools, but its domain is distinct.

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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TDQS

A3.8/5.0
Disambiguation4/5

Tools are grouped into clear domain prefixes (crypto, data, developer, document, research, web) and each tool name describes a specific function; however, a few umbrella tools like web.full-audit and data.contract overlap with their more targeted counterparts, creating minor ambiguity.

Naming Consistency5/5

All tool names follow a consistent pattern: a domain prefix, a dot, and a hyphenated lowercase compound name (e.g., crypto.base-block-inspect, web.seo-audit). This makes naming predictable and easy to scan.

Tool Count1/5

At 63 tools, the surface area is very large and exceeds the 50+ threshold for extreme mismatch. While the tools are organized into six domains, the sheer number makes it difficult for an agent to select efficiently, and some tools are bundled combinations of others.

Completeness5/5

Each domain offers a thorough set of operations: crypto covers address, account, block, contract, events, gas, and transaction inspection; data covers cleaning, conversion, schema, and validation; developer covers code review, dependency/license audits, and test generation; research covers SEC, OFAC, GLEIF, and USAspending; web covers extraction, SEO, security, and performance. No obvious dead ends exist for the read-only/inspection purpose.

Resources