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Search Vlak components

search_components
Read-onlyIdempotent

Find components by name, title, description, alias (AI Elements, shadcn/ui, Radix, and common names such as PromptInput, Chain of thought, Sonner, Drawer, Combobox), or rs-* class. Spacing, punctuation and capitalization do not affect matching. Returns matches ranked by field.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
termYesSearch term, e.g. "menu", "snackbar", "rs-input"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hitsYes
termYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnly, idempotent, and non-destructive hints, so the behavior bar is lower. The description adds valuable normalization behavior: spacing, punctuation, and capitalization don't affect matching. It also discloses that results are ranked by field, which is beyond what the annotations or schema state.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core purpose, and follows with matching details and ranking behavior. The alias list adds specificity without bloat and every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the small parameter surface, rich input-schema, output schema, and annotations, the description adequately completes the picture. It addresses the non-obvious matching semantics, though it doesn't mention potential null results or pagination behavior—minor gaps not essential to selecting the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

While the schema already covers 100% of the parameter, the description dramatically expands term semantics by revealing it can match aliases like shadcn/ui or common names, plus rs-* classes. This goes beyond the schema's simple examples and meaningfully improves correct invocation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource, 'Find components', and goes on to enumerate the searchable fields (name, title, description, alias, rs-* class). This clearly differentiates it from sibling tools like get_component (exact fetch) or list_components (enumeration).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a clear sense of what kinds of terms can be searched (fuzzy/alias/rs-*), so it implies usage for locating components without exact IDs. However, it never explicitly names when to prefer this over get_component or list_components, leaving alternative selection to inference.

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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