按自然语言关键词推荐配色（中英文均可），例如「护眼的深色记账 App」「清新博客」。会说明每个结果命中了什么。
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": {
"query": "<query>"
},
"name": "suggest_palette"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 最多返回几条，默认 5 | |
| query | Yes | 关键词，空格分隔，如「深色 记账」 | |
| platform | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose two useful behavioral facts: queries work in Chinese or English, and results explain what each match hit. It says nothing about determinism, whether results are cached palettes or generated, or any rate/limit behaviour beyond the schema's default.
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 with the core action front-loaded, followed by examples and one return-value note. No filler, though the examples and the '命中' note could be tightened.
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 read-only suggestion tool with no output schema and no annotations, the description should at least clarify the platform parameter's effect and what a returned suggestion contains. It covers the return semantics loosely ('会说明每个结果命中了什么') but leaves the platform dimension and result shape under-specified.
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 67%: query and limit are self-documented, but the platform enum (app/web/miniapp) is unexplained in both schema and description. The description does add real value by stating query accepts Chinese or English space-separated keywords, which goes beyond the schema's example.
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?
Names a specific verb (推荐) and resource (配色) plus the input modality (自然语言关键词), with two concrete examples that make the intent unambiguous. It does not explicitly contrast itself with the read-oriented siblings (get_palette, list_palettes, get_css_variables), so an agent must infer the keyword-vs-lookup distinction.
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 examples (「护眼的深色记账 App」) imply when this tool fits — when the user describes a mood or product rather than naming a palette — but there is no explicit 'use this instead of X when...' routing. No prerequisites or exclusions are stated.
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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