search_componentsFind Quasar Framework components by plain-language query or slug, returning up to 20 ranked matches with Free or Paid access labels.
Search Components by a plain-language query, e.g. "pricing table with a monthly/yearly toggle" or a slug. Returns up to 20 matches, best first, each with its Free or Paid access.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | What you are looking for |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only cover readOnlyHint, so the description carries the return-behavior burden — and it does disclose result cap (up to 20), ordering (best first), and per-result payload (Free or Paid access). What's missing is what happens when the corpus exceeds 20 matches (truncation vs. pagination), which matters for a capped search.
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, front-loaded with the verb and resource, then query forms, then return shape. No filler and nothing repeated from the schema.
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 one-param, read-only search with no output schema, the description covers input formats, result count, ranking, and result fields — essentially everything needed to call it. The remaining gap is sibling routing and behavior beyond the 20-result cap.
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 coverage is 100% and the single param is documented as 'What you are looking for', so baseline is 3. The description earns the extra point by supplying concrete query forms — natural-language descriptions like 'pricing table with a monthly/yearly toggle' and slug input — which tells the agent the accepted syntax 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?
States a specific verb ('Search') and resource ('Components') plus the query form accepted (plain-language or slug). It doesn't name the sibling tools, so the distinction from list_components (enumerate all) and get_component (fetch one by id) is left implicit rather than explicit.
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 example query illustrates usage, so the agent can infer 'use this when you have a descriptive need rather than an id'. But there is no explicit when-to-use/when-not and no pointer to list_components for browsing or get_component for full detail, which is the main routing decision an agent faces here.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.