Search components across libraries

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

With no annotations, the description carries full burden. It discloses synonym-aware behavior (modal/dialog, dropdown/select), the return format (registry, name, type, title, description), and clearly states it does NOT return source code. This is comprehensive and leaves no surprises.

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 concise (four sentences), front-loads the core purpose, and efficiently uses examples and hints. Every sentence adds value without redundancy.

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 the tool has 4 parameters, full schema coverage, no output schema, the description explains the return format (lightweight list with fields) and ranking. It is complete enough for an agent to use the tool effectively without additional information.

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%, so baseline is 3. The description adds value by explaining the natural-language nature of the query, giving synonym examples, and clarifying optional filters with concrete values (ui, block, component, hook). It enhances understanding beyond schema alone.

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 across component libraries for components matching a natural-language query. It provides examples ('pricing table', 'date picker') and explicitly distinguishes from sibling tool get_component by stating it returns a lightweight list, not the source. This leaves no ambiguity about what the tool does.

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 description advises to 'Pick the best match, then call get_component to fetch its real code,' which provides a clear usage pattern. However, it does not explicitly state when not to use this tool or specify alternatives beyond get_component, so a slight deduction from a perfect score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.