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mcp-easy-ai__wp_count_posts

Read-only

Returns post counts grouped by status (publish, draft, pending, future, private, trash, auto-draft, inherit) for a given post type. Optional: post_type (default 'post'). Returns { post_type (the post_type echoed back), counts } where counts is keyed by status with INTEGER values (WP returns numeric strings; this tool casts them). Useful for dashboard-style summaries — wp_list_posts only returns one filtered total per call. Every status is counted only for a user who can edit that post type (its own capability, e.g. edit_pages for pages); anyone else gets only the published count of a public type, with a note saying so, and is refused a type that is not public. Through Royally: its server marks it read-only, so it runs straight away.

Input Schema

NameRequiredDescriptionDefault
site_idNoSite to run this tool on: 8ef2e52b-bd07-4671-a363-ebe8b480b65c (https://demo.royalplugins.com)
post_typeNoPost type slug. Defaults to "post".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the readOnly/non-destructive annotations, the description discloses that numeric strings are cast to INTEGER, that every status is only counted for a user with the matching capability (e.g. edit_pages), that other users get only the published count plus a `note`, and that non-public types are refused. Those are non-obvious authorization and data-shaping behaviors an agent cannot get from the annotations.

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?

Front-loaded with the core behavior and return shape, then permission caveats. It is a single dense paragraph with little waste, though the Royally/read-only note is somewhat redundant with annotations.

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?

No output schema exists, so the description carries the return contract itself — { post_type, counts } with integer values — and adds the permission edge cases and the `note` field. That is enough for an agent to call it and interpret results correctly.

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?

Schema coverage is 100%, so both the site_id enum and post_type are already documented. The description restates the post_type default and adds that the value is echoed back in the result, but contributes little semantic depth beyond the schema.

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 with scope: post counts grouped by status for a given post type, and enumerates the statuses returned. It explicitly distinguishes itself from wp_list_posts, which 'only returns one filtered total per call,' so an agent can pick between them without opening schemas.

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?

Gives a concrete use case ('dashboard-style summaries') and names the alternative (wp_list_posts) with the condition that separates them. It lacks an explicit statement of when not to use it, but the routing guidance is clear.

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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