get_componentDocs for one item: install command, usage example, props, keyboard, accessibility and notes.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The item's slug, e.g. reaction-bar – add -clean for the clean style, e.g. ai-answer-clean |
Changes observed during successful MCP inspections.
Input schema / properties / slug / descriptionPrevious value: -"The item's slug, e.g. reaction-bar"New value: +"The item's slug, e.g. reaction-bar – add -clean for the clean style, e.g. ai-answer-clean"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the disclosure burden. It does tell the agent the shape of the returned content (install command, usage example, props, keyboard, accessibility, notes), which is valuable since there is no output schema, but it says nothing about auth requirements, errors for an unknown slug, or whether the response is static or versioned.
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?
A single front-loaded clause listing the returned content with zero filler. It is efficient, though the fragment form is terse and leaves no room for routing guidance.
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-parameter lookup with full schema coverage and no output schema, enumerating the returned sections substantially compensates for the missing output schema. The gap is the absence of any guidance distinguishing it from get_source/search_components.
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 description coverage is 100%, and the single slug parameter is documented in the schema, including the '-clean' style suffix convention. The description adds no additional parameter meaning, so baseline 3 applies.
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 clear resource and scope: documentation for a single item, enumerating what that documentation contains (install command, usage example, props, keyboard, accessibility, notes). The singular 'one item' implicitly contrasts with list_components/search_components, but the description never names those siblings or the get_source alternative, so the differentiation is left to inference.
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?
No explicit when-to-use or when-not-to-use guidance. The phrase 'for one item' implies a single-item lookup versus listing/searching, and the slug-driven schema reinforces that, but the agent must infer when to pick this over get_source (source vs docs). Usage is implied, not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.