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Nucleo for WordPress

Nucleo for WordPress

by nucleowp
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Hybrid

nucleo-model-get

Read-onlyIdempotent

Retrieves the saved WordPress content model and shows usage counts plus unmodeled post types or taxonomies, so agents can inspect what the model declares and what remains unmodeled.

Instructions

Returns the saved content model (post types, taxonomies, field groups), how many items use each part, and "unmodeled": the post types and taxonomies of the site that the model does not declare, with registeredBy (wordpress, or plugin-or-theme: registered by another plugin or the theme, so model-set cannot declare that slug; it can add a field group to it). Model format: catalog-get {topic: model}.

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-model-get"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the description's job is to disclose content, which it does well: usage counts per part and a defined "unmodeled" set with registeredBy semantics (wordpress vs plugin-or-theme). It stops short of mentioning behavior for an empty/unset model, caching, or any error/edge case.

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

Conciseness3/5

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

The key fact (what it returns) is front-loaded, which is right, but the main sentence is a long run-on with nested parentheticals that takes effort to parse. The trailing "Model format: catalog-get {topic: model}." reads as an afterthought and is the least clear sentence relative to its importance.

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

Completeness4/5

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

With no output schema, the description carries the return-shape burden and largely meets it by naming every section of the result, including the non-obvious "unmodeled"/registeredBy part. For a zero-parameter read tool with safety annotations, this is close to complete; only empty-state behavior is unaddressed.

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 tool takes no parameters, so there is no parameter meaning to add; the schema itself is closed and fully described. Baseline of 4 applies since the description cannot and need not compensate for anything here.

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?

States a specific verb and resource ("Returns the saved content model") and then enumerates exactly what that model contains: post types, taxonomies, field groups, per-part usage counts. It goes further by naming the extra "unmodeled" section, so an agent knows the payload shape without opening anything else.

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?

Usage is only implied: it is clearly the read side of the model pair, and it notes that for plugin/theme-registered slugs model-set cannot declare the slug but can add a field group. There is no explicit "call this before model-set" or "use this instead of model-validate" instruction, so the when-to-use decision is left to inference.

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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