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Glama

ZadenWorks

by io.github.ZadenGG

validate_structured_data

Validate a page's JSON-LD structured data and its social preview tags. Reports which schema.org types are present, whether each carries the fields Google's rich results require, whether any JSON-LD block fails to parse as JSON, and whether Open Graph and Twitter Card tags are complete. Useful before publishing, or to diagnose why a page renders no preview card when shared. Returns a 0-100 score, a letter grade and a prioritised issue list. Up to 10 URLs per call. Paid: $0.01 per call in USDC on Base via x402 -- call once without x_payment to receive the payment challenge.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesPages to validate (max 10)
x_paymentNoOptional X-PAYMENT header value from a completed x402 payment. Omit on first call to receive the payment challenge; complete the payment with your x402 wallet tooling, then retry with this set.

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Discloses the payment requirement, the $0.01 per call cost, the x402 payment flow, and the need to first call without x_payment to receive a challenge. Also describes the output format (score, grade, issue list). It does not mention rate limits or error handling, but the key behaviors are covered.

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 a single, information-dense paragraph that covers all necessary aspects without fluff. While slightly long, it is efficient and flows logically from purpose to details to payment.

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 the payment complexity and the multiple validation aspects, the description provides sufficient context for invocation, output, and use cases. It explains the payment challenge flow, output format, and typical scenarios, making it self-contained for an agent.

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?

The schema descriptions fully cover both parameters, including the max 10 URLs limit and detailed x_payment instructions. The tool description reinforces the payment workflow, adding value beyond the schema.

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 validates JSON-LD structured data and social preview tags, and enumerates specific checks (schema.org types, required fields, JSON parse, Open Graph, Twitter Card). This distinguishes it from sibling tools like audit_seo which likely cover broader SEO concerns.

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 notes usefulness before publishing and for diagnosing missing preview cards when shared. While it does not directly compare to sibling tools, the specificity of the described checks makes its niche evident.

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

A4.1/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose, from SEO audits to link checking, content comparison, accessibility scans, structured data validation, and claim verification. No two tools overlap in function.

Naming Consistency4/5

Names mostly follow a consistent verb_noun snake_case pattern (audit_seo, check_links, compare_pages). Minor deviations like rank_x402_services and list_rank_categories are slightly less uniform but still readable and predictable.

Tool Count5/5

14 tools cover a broad but focused range of web page analysis and auditing workflows without feeling bloated. The count is well within the ideal 3-15 range for a specialized service.

Completeness5/5

The tool surface is remarkably complete for the domain: covers SEO, sitemaps, links, content, rendering, accessibility, structured data, claims, and monitoring. No critical dead ends or obvious missing operations for typical use cases.

Resources