Everything needed to write a correct call site for one component: props with types, defaults and value domains, platform applicability, dependencies — and the runtime rules that apply to it. Always read the rules; getting props right and rules wrong still ships a blank screen.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | e.g. "button" |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It provides useful context about what the tool returns, including props types, defaults, value domains, platform applicability, dependencies, and runtime rules. The warning that getting props right but rules wrong still ships a blank screen is a meaningful behavioral cue beyond the schema, though it does not discuss side effects, errors, or access requirements.
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 two sentences with no filler. It front-loads the main purpose and then adds a high-value warning that guides usage. Every clause earns its place, and the informal closing reinforces an important behavioral point without bloating the 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 tool with one parameter and no output schema, the description gives a solid inventory of what will be returned: props with types/defaults/domains, platform applicability, dependencies, and runtime rules. It is complete enough for an agent to know what to expect and how important the rules are, though it stops short of describing the exact response structure or error behavior.
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?
The input schema has 100% description coverage for the only parameter, slug, including an example. The description adds the context that the tool is for 'one component,' which reinforces the slug's role, but it does not provide additional parameter-level meaning beyond the schema. This aligns with the baseline for high schema coverage.
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 identifies the tool's scope: it returns everything needed to write a correct call site for a single component, including props, defaults, platform applicability, dependencies, and runtime rules. It distinguishes itself from siblings like list_components and find_component by focusing on one component, though it never states an explicit verb like 'retrieves' or 'returns,' which keeps it from being a 5.
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 tells the agent when to consult this tool: when writing a call site for a component. It also gives a strong directive to always read the rules and explains the consequence of ignoring them. It does not explicitly name alternatives or state when not to use it, so it is one step below full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.