Search public canonical Wikivibe articles about AI coding, agents, MCP, tools, SEO/GEO, bots, deployment and product workflows.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | Search phrase. | |
| locale | No | ru |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden of behavioral disclosure. It only describes the scope of articles but omits details like authentication, rate limits, read-only nature, or search behavior (e.g., full-text vs title-only).
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 concise sentence (18 words) that is front-loaded with the verb and resource, containing no redundant information.
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 three parameters and no output schema, the description lacks essential context such as default behavior, return format, pagination, or how the limit and locale affect results.
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 only 33% (only 'query' has a description). The tool description does not elaborate on parameters like 'limit' or 'locale', nor does it provide usage examples or clarify their semantics beyond the schema.
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 verb 'Search' and the resource 'public canonical Wikivibe articles', and lists specific topics (AI coding, agents, MCP, etc.), distinguishing it from sibling tools like search_design_templates or search_skills.
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?
No guidance is given on when to use this tool versus alternatives like list_latest_articles or search_skills, nor are there any contextual hints about when not to use it.
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.
Each tool targets a distinct resource and action: get for single items, list for collections, search for finding, and recommend for project-based suggestions. No two tools have overlapping purposes.
All tool names follow a consistent verb_noun snake_case pattern (e.g., get_article, search_skills). The verbs and nouns are clearly descriptive and uniform across the set.
With 9 tools, the set is well-scoped for a public knowledge server covering articles, design templates, and AI skills. Each tool serves a clear role without redundancy or overload.
The tool set provides comprehensive read and search operations for all three content types, plus a recommendation feature. Minor gaps exist, such as no listing of all articles by section or pagination support, but core workflows are covered.
