search_components

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

With no annotations, the description carries the full burden, and it delivers: it discloses case-insensitive matching, the typed missing_argument refusal for a missing query, and that an empty result returns count 0 rather than an error. It also explains why the argument is optional, which is valuable.

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?

Two tight paragraphs, purpose first, then behavioral edge cases. The parenthetical rationale earns its place by explaining the optional-argument design. No wasted words.

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 one optional parameter, the description covers purpose and edge cases well. However, with no output schema, it doesn't specify the success return payload (e.g., component objects, count, pagination), so agents must guess at the result shape beyond count 0.

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 0%, so the description must enrich the bare optional string parameter. It does by defining query as a substring, specifying case-insensitivity, and documenting the missing-query behavior. It doesn't specify length or format limits, but the semantics are clear.

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 and resource: search components by substring across name, category, tags, and verified descriptions. This clearly identifies the operation and scope, but does not explicitly distinguish it from sibling tools like find_components or list_components, which may overlap.

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 implies when to use this tool: when a substring match across those fields is needed. However, it offers no explicit comparison to siblings like find_components or list_components, nor any 'when not to use' guidance.

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