slug-generatorTurn a title into a clean, SEO-friendly URL slug: lowercase, hyphenated, accent-safe, optional stopword removal.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| separator | No | - | |
| removeStopwords | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, so the description does not need to restate safety. It adds valuable behavioral details: lowercasing, hyphenation, accent handling, and optional stopword removal, which are not present in the annotations or schema. No contradiction exists.
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?
A single, well-structured sentence that front-loads the primary action and includes key features. No unnecessary words, making it efficient for an AI agent to parse quickly.
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?
For a simple transformation tool with no output schema, the description covers input, processing, and options. The return value (a slug string) is implicit. Combined with the read-only annotation, the tool is fully understood in context.
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?
Schema description coverage is 0%, so the description carries the burden. It mentions 'stopword removal' (mapping to removeStopwords) and 'hyphenated' (implying separator default), but it does not explain the separator parameter or provide examples. It partially compensates but leaves some param semantics implicit.
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's function: transforming a title into a URL slug. It specifies the output characteristics (lowercase, hyphenated, accent-safe) and optional stopword removal, making it distinct from sibling tools like headline-generator or meta-description-generator.
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 when to use the tool (when a clean, SEO-friendly slug is needed from a title). It provides clear context but does not explicitly mention alternatives or exclusions. The purpose itself is sufficiently self-explanatory for typical use cases.
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.