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Fabrement

Get SEO state

fabrement-get-seo
Read-only

Read the SEO state: always yoast {active, version}; with contentId — the record's stored Yoast fields, effective output (title, description, canonical, robots) and the FULL schema graph it emits (and primaryTerms: the main term per taxonomy, for breadcrumbs); with termId — a term archive's stored and effective SEO; with archive (a post type) — its archive's stored and effective SEO; with postType — its defaults and schema template; with neither — the site settings and knowledge graph. Call it FIRST (is Yoast active?) and AFTER a write to verify. Rules: get-skill-doc {id:"seo-contract"} — read it before the first call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
termIdNoA term: the stored and effective SEO of its archive page.
archiveNoA post type: the stored and effective SEO of its archive.
postTypeNo
contentIdNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
siteNo
termNo
yoastYes
archiveNo
contentNo
postTypeNo
typesWithSchemaNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=true; the description adds real behavioral context beyond that — the stored-vs-effective distinction, the FULL schema graph emitted, primaryTerms for breadcrumbs, and the site settings/knowledge graph fallback. The FIRST/AFTER-write guidance and skill-doc prerequisite further clarify operational behavior.

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 selector list is front-loaded and dense but every clause carries information; the Rules sentence is separated out. It is a long single sentence with em-dash chaining, slightly heavy, but not padded.

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?

Output schema exists, so return-shape detail is not required, and the description still covers per-selector behavior plus prerequisites. For a read-only inspection tool with a rich output schema, this is essentially complete.

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?

With only 50% schema description coverage, the description compensates by explaining each selector's meaning — termId for a term archive, archive for a post type archive, postType for defaults/template, contentId for the record's Yoast fields, and 'neither' for site settings. This meaningfully exceeds what the schema documents.

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?

The description states a specific verb (Read/Get) and resource (SEO state) and enumerates exactly what is returned for each selector (contentId, termId, archive, postType, neither). It reads distinctly from write-oriented siblings like set-seo/set-seo-defaults, though it never names an alternative explicitly.

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?

It gives clear operational guidance: 'Call it FIRST (is Yoast active?) and AFTER a write to verify,' plus a prerequisite rule to read the seo-contract skill doc before the first call. It does not name a sibling to use instead in any case, so it stops short of explicit alternatives.

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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