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post_schema_audit

Audit schema.org structured data (JSON-LD) for Google rich-result readiness. POST a URL or raw JSON-LD; returns detected types, missing required/recommended fields, honest rich-result status (flags deprecated types like FAQ/HowTo), and fix suggestions. Covers Product, Review, Article, Recipe, VideoObject, LocalBusiness. Current to 2026 Google guidance. ($0.005 per call, paid via x402)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoPublic URL to fetch and audit its JSON-LD
jsonldNoRaw JSON-LD object to audit directly (alternative to url)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
foundNo
auditedNo
detectedNo
with_issuesNo

Schema Changelog

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

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations indicate readOnlyHint=false, meaning the tool might not be read-only, but the description does not clarify potential side effects (e.g., whether it logs data or modifies state). It does state the cost and payment method, which adds some transparency. No contradiction with annotations, but more detail on data handling or security would improve clarity.

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 two sentences long, front-loading the core purpose and method in the first sentence, with additional specifics (coverage, updates, cost) in the second. Every sentence adds value without redundancy or 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 the tool's complexity (auditing multiple schema types, output with missing fields and suggestions) and the presence of an output schema (not shown), the description covers all essential aspects: input options, output contents, coverage, recency, and cost. It is complete for an agent to understand what the tool does and what it returns.

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 both parameters with descriptions (100% coverage). The description restates that you can POST a URL or raw JSON-LD, but adds no new meaning beyond what the schema provides. Baseline 3 is appropriate as the schema does the heavy lifting.

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 audits schema.org structured data for Google rich-result readiness. It specifies the action (audit), the resource (JSON-LD), and the output (detected types, missing fields, status, suggestions). It distinguishes itself from sibling tools like post_schema_generate (which generates schema) and get_seo_full_audit (which audits overall SEO, not just schema).

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?

The description provides clear context on when to use: for auditing schema.org data for rich results. It mentions coverage of specific types and current guidance. However, it does not explicitly state when not to use this tool or suggest alternatives (e.g., for non-schema audits or different output formats). The mention of cost is useful but not about usage boundaries.

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

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but the SEO-related tools (head_check, full_audit, site_audit, etc.) overlap in scope, potentially causing confusion despite clear descriptions.

Naming Consistency5/5

Tool names consistently follow a get_/post_/delete_ verb pattern with descriptive noun phrases (e.g., get_seo_head_check, post_store_collection), with no mixing of naming conventions.

Tool Count2/5

With 46 tools covering a wide breadth of domains (SEO, accessibility, music, crypto, linting, etc.), the count is excessive for a single server, feeling unfocused and heavy.

Completeness4/5

The tool set covers most core operations for each sub-domain, but minor gaps exist (e.g., missing update for datastore, limited music operations).