Search @marmoui/ui by keyword (e.g. "form", "table", "dialog", "avatar"). Preferred discovery tool — returns the 5-8 most relevant components for a need. Call this before get_component_info when unsure which component to use.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum results to return (default: 10) | |
| query | Yes | Search query — matches against component names, descriptions, categories, and prop names |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It does reveal a key behavior: 'returns the 5-8 most relevant components.' However, it does not state whether the tool has side effects, requires authentication, or handles edge cases like no matches. The non-destructive nature of a search is implied but not explicit, and no additional safety or side-effect information is given.
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 two sentences long, front-loaded with the core action, and every clause adds value. It is concise without unnecessary elaboration.
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 search tool with 2 params and no output schema, the description covers the core purpose, usage sequence, and a behavioral trait (result count). It does not specify the return format or edge cases, but these are not critical for a discovery tool. Overall, it is sufficiently complete for an agent to invoke it correctly in most scenarios.
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 100%, so the baseline is 3. However, the description adds no meaningful parameter semantics and even introduces potential conflict: it claims 'returns the 5-8 most relevant' while the schema's limit parameter defaults to 10, implying up to 10 results. This lacks clarity and could mislead an agent about result count.
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 action: 'Search @marmoui/ui by keyword' with concrete examples. It distinguishes itself from sibling tools like list_components and get_component_info by calling itself the 'Preferred discovery tool' and explicitly instructing to call it before get_component_info when uncertain which component to use.
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?
Provides explicit usage guidance: 'Call this before `get_component_info` when unsure which component to use.' This establishes a clear workflow and alternative. The phrase 'Preferred discovery tool' further signals when this should be used over other listing or info-gathering tools.
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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Most tools have distinct purposes, but there is some overlap between review_generated_code and validate_component_usage, and between list_components and search_components. However, descriptions clearly differentiate their intended use cases, reducing ambiguity.
All tools follow a consistent verb_noun pattern with snake_case (e.g., get_component_info, generate_component, review_generated_code). The naming is predictable and clearly indicates the action.
14 tools is well-scoped for a UI design system assistant. It covers component discovery, detailed info, design guidelines, theme, code generation and validation, and prototype management without being overwhelming.
The tool set covers the full workflow: discover components, get patterns, get design guidelines, generate and validate code, get tenant theme, deploy prototypes and collect feedback. No obvious gaps for the intended usage scenario.