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Google Search Console MCP Server

gsc_audit_jobposting_schema

Audits JobPosting JSON-LD schema on given URLs, validates against Google's checklist, and dry-runs Indexing API eligibility without publishing changes.

Instructions

Read-only JobPosting JSON-LD audit and Indexing API eligibility dry run.

This tool fetches only property-scoped URLs, blocks unsafe/private targets,
does not follow redirects, parses JSON-LD JobPosting objects from static HTML,
validates a minimal Google JobPosting checklist, and returns what Indexing API
action would be eligible in a dry run. It never calls the Indexing API, never
publishes URL_UPDATED or URL_DELETED, never writes files, and never mutates
Search Console.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYes
max_urlsNo
site_urlYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description carries full burden. It explicitly states multiple behavioral traits: read-only, blocks unsafe/private targets, does not follow redirects, never calls Indexing API, never mutates Search Console. These are clear and accurate.

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 a single, dense paragraph that is front-loaded with the key purpose. Every sentence adds value: it lists actions, constraints, and what it returns. No redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description provides good behavioral detail but lacks parameter explanations (site_url, urls, max_urls). Given that the input schema has no descriptions and 3 parameters, the description should clarify what each parameter represents. The output schema exists, so return values are covered.

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

Parameters2/5

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

Schema description coverage is 0%, but the description does not explain the parameters (site_url, urls, max_urls). It only mentions 'fetches property-scoped URLs' which implies url is a list, but does not clarify format or meaning. The description fails to compensate for missing schema descriptions.

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 it's a read-only audit of JobPosting JSON-LD and a dry run for Indexing API eligibility. It specifies the scope (property-scoped URLs), actions (fetches, blocks unsafe, parses, validates), and output (eligible action). It is distinct from sibling tools like build_indexing_action_queue or inspect_url_enhanced, which have different purposes.

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

Usage Guidelines3/5

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

The description implies usage for auditing job posting schema and performing a dry run, but does not explicitly state when to use this tool versus alternatives (e.g., inspect_url_enhanced, build_indexing_action_queue). No exclusions or when-not-to-use guidance is provided.

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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