取一套配色的 CSS 自定义属性（可直接粘进项目），含语义化变量名。
Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {
"slug": "<slug>"
},
"name": "get_css_variables"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | 配色 slug | |
| platform | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It conveys the output shape (CSS custom properties with semantic names) but says nothing about read-only status, required auth, whether an invalid slug errors or falls back, or per-platform output differences — a significant gap for an unannotated tool.
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 compact sentence that front-loads the resource and the key output characteristic. Nothing is padded, though it is arguably undersized given the undocumented platform parameter.
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?
With no output schema, the description partially compensates by characterizing the return value (CSS custom properties, semantic names, paste-ready). But it omits any explanation of the platform parameter's effect and any routing guidance among the three sibling palette tools, leaving the definition only minimally viable.
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 only 50%: 'slug' is briefly glossed as '配色 slug' while 'platform' has an enum but no description at all. The tool description never mentions either parameter, so it does not compensate for the documentation gap — notably, nothing explains what selecting 'app' vs 'web' vs 'miniapp' does to the output.
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: retrieving CSS custom properties for a color scheme, with the useful detail that they are directly pasteable and semantically named. It is clear what the tool returns, though it never distinguishes itself from the sibling get_palette, leaving the agent to infer that this one is the CSS-format export variant.
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 parenthetical '(可直接粘进项目)' implies a usage context (export-ready CSS for embedding in a project), which hints at when to prefer this over get_palette. However, there is no explicit when-to-use statement, no when-not-to-use, and no reference to any sibling tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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