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nucleo-quality-scan

Idempotent

Scan published pages in batches for duplicate titles and H1s, orphan pages, breadcrumb conflicts, and repeated sections, returning SEO, accessibility, and performance scores with blocking errors.

Instructions

Checks all published documents in batches: duplicate title and h1, orphan pages without internal links, breadcrumbs duplicated by the SEO plugin, sections repeated with different visibility. Returns the site issues, the SEO, accessibility and performance scores of the pages in the batch, the rules with their severity (rules), the number of pages with blocking errors (errorPages) and the next page (next).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "nucleo-quality-scan"
  }
}

Input Schema

NameRequiredDescriptionDefault
pageNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare idempotent=true and destructive=false, but also readOnlyHint=false, which is notable for a 'scan'. The description adds useful context about what is checked and what is returned, yet it does not explain why the tool is not read-only, whether there are side effects, batch size, permissions, or performance impact.

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 purpose is front-loaded in a single dense sentence, followed by enumerated checks and return fields with little filler. It could be split for readability, but every clause contributes useful information.

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?

For a paginated scan with no output schema, the description covers the checks performed and most return fields, including 'next'. However, it leaves the sole input parameter undefined and does not reconcile the non-read-only annotation, so it is not fully complete for confident invocation.

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?

There is one optional parameter, 'page', with 0% schema description coverage. The description mentions 'in batches' and a returned 'next page (next)', but never defines what 'page' means, how to use 'next' with it, or what batch size is applied, so it does not compensate for the undocumented parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Checks') and resource ('all published documents in batches'), and enumerates the checks performed, including duplicate title/h1, orphan pages, breadcrumbs, and repeated sections. It does not explicitly differentiate this scan from the sibling nucleo-quality-check, so it falls short of a 5.

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 batch-wide quality scanning and hints at pagination through the returned 'next page (next)', but it gives no explicit when-to-use, when-not, or alternative tool guidance. Usage is inferable but not directly guided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.