content-coverage-checkerContent Coverage Checker: List the terms and entities an article targeting a keyword is expected to cover. (free, AI-generated, rate-limited).
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | No | ||
| language | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds 'free, AI-generated, rate-limited' beyond the readOnlyHint annotation, giving valuable operational context. It also indicates the output is predictive ('expected to cover'). However, it does not reveal any edge-case behavior or error handling, but the annotation already covers mutability.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence followed by a concise parenthetical of key qualifiers. It is front-loaded with the tool's purpose and contains no redundant phrases or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description does not specify the return format (e.g., list of strings) or how language affects results. It covers the basic function but is missing important contextual details for a tool with zero schema coverage and no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description must compensate for parameter meanings. It only hints at 'keyword' via the phrase 'targeting a keyword' and entirely omits the 'language' parameter's role or valid values. This leaves a gap for agents needing to set both parameters correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists terms and entities for an article targeting a keyword. The verb 'List' and resource 'terms and entities' make the purpose explicit, distinguishing it from content generators or other SEO tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for content planning by referencing 'an article targeting a keyword,' but it does not explicitly state when to use this tool versus alternatives like blog-outline-generator or content-brief-generator. No exclusions or alternative tool mentions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes, but word-counter and character-counter overlap heavily, and meta-tag-generator subsumes several other generators (title, description, canonical). The sheer number of adjacent content generators creates some ambiguity, though descriptions generally clarify.
Tool names are inconsistent: some use snake_case (create_site, get_article, list_articles) while others use hyphenated lowercase (ad-copy-generator, meta-tag-generator, robots-txt-generator). This mixing of conventions makes it hard for an agent to predict the name for a given action.
With 59 tools, the server is heavily over-scoped for a typical MCP server. Many tools are similar (various calculators, many content generators) and could be consolidated, making the surface bloated and harder to navigate.
The server covers a broad range of SEO tasks: site management, article generation/publishing, analytics, technical SEO, and content tools. However, there are gaps such as missing update/delete operations for articles and no backlink analysis, leaving some workflows incomplete.