Vaneform

lookup_keyword

Read a US/EN keyword brief: monthly searches, difficulty, CPC, and Google occupancy. Pro-only. At most 30 Google results. A cache hit is free; a successful miss spends 60 credits. After trimming, longer than 200 characters is invalid. Matching uses the lowercased, space-collapsed first 80 characters. Use for 关键词查询.

Tool call template

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": {
      "q": "<q>"
    },
    "name": "lookup_keyword"
  }
}

Input Schema

Name	Required	Description	Default
`q`	Yes	Keyword such as google or apple. After trimming, longer than 200 characters is invalid. Matching keeps the lowercased, space-collapsed first 80 characters.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 15, 2026

TDQS

A3.9/5.0

Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses the Pro-only plan requirement, the 30-result cap, the caching economics (free cache hit vs. 60 credits on a successful miss), and the matching/validation rules. These are exactly the operational facts an agent needs before invoking a metered lookup.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded and the behavioral facts follow in dense, information-bearing sentences. It loses a point for the redundant trailing 'Use for 关键词查询' and for restating the 200-character trimming rule that already appears in the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter read tool with no output schema or annotations, the description covers cost, limits, scope, and input validation adequately. Minor gaps remain around error behavior and whether the brief structure differs from the listed fields, but nothing critical to correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the single parameter, and the description's trimming and 80-character matching notes duplicate what the schema already states. Baseline 3 is appropriate since the schema does the heavy lifting and the description adds no new parameter meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource ('Read a US/EN keyword brief') and enumerates the returned fields (monthly searches, difficulty, CPC, Google occupancy), which clearly separates it from lookup_domain and the compare_* tools. There is no explicit sibling routing statement, but the resource identity makes the distinction obvious.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage context is implied through scope constraints: US/EN only and Pro-only, which tell the agent when the tool is applicable. However, 'Use for 关键词查询' is a tautological restatement of the tool name rather than guidance, and no alternatives or when-not conditions are named.

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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