Read one public Wikivibe AI-agent skill by slug, absolute URL or localized path.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Absolute skill URL or localized path. | |
| path | No | Skill path, for example /ru/skills/astro-performance-audit/. | |
| slug | No | Skill slug. | |
| locale | No | ru |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It states 'Read' (read-only) and 'public' (no auth), but omits error behavior (e.g., missing skill) and response format. This is insufficient for mutation-agnostic agents.
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?
One sentence, 12 words, no redundancy. Front-loaded with verb and resource, immediately clear. Every word earns its place.
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?
No output schema provided. Description does not specify return structure, error handling, or which parameter takes precedence. For a 4-param tool with no annotations, this leaves significant gaps for correct invocation.
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 75%, so baseline is 3. The description adds that the skill is public and can be fetched by any of the three identifier parameters, but does not add semantics beyond what the schema already provides (e.g., no hint on which param to prefer).
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 uses the verb 'Read' with direct object 'one public... skill' and specifies identification methods (slug, absolute URL, localized path), clearly distinguishing from sibling tools like get_article 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 explicit guidance on when to use versus alternatives (e.g., search_skills for discovering skills). The purpose is implied but not reinforced with when-not or exclusions.
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.
