find_components

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

The description goes beyond typical expectations by explaining the behavior for missing and unknown categories, including the unusual design choice of declaring the parameter optional to ensure errors are returned as payloads rather than validation crashes. This is significant behavioral context that helps an agent understand error handling.

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 and well-structured. It front-loads the core purpose in the first sentence, then provides essential behavioral details in a clear parenthetical note. Every sentence adds value, and there is no wasted text.

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 one-parameter tool with no output schema or annotations, the description covers the essential usage and error handling. It doesn't describe the return format or list valid categories, but those might be accessible through sibling tools like list_categories, and the closed vocabulary hint is sufficient for an agent to know how to proceed.

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?

With 0% schema coverage, the description must compensate, and it does: it explains that category is a closed vocabulary and describes the error behaviors for missing and unknown values. It could mention that category is a string, but the schema already shows that, and the description adds meaningful semantics about the allowed values (closed set) and error handling.

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 states a clear verb and resource: 'Find all components in one category', and clarifies that the category is a closed vocabulary. It distinguishes itself from sibling tools by focusing on category-based retrieval rather than search or listing all components, though it doesn't name a specific sibling.

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 clearly indicates when to use this tool: when you need components for a specific category, with a closed vocabulary. It doesn't explicitly name alternatives or exclusions, but the closed vocabulary hint and the semantic distinction from search_components and list_components provide adequate guidance.

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