Find relevant data features by entering a keyword. Returns a list of matching attributes for analyzing Japanese horse racing data.
キーワードで特徴量を検索
Args:
keyword: 検索キーワード（例: "人気", "距離", "騎手"）
Returns:
該当する特徴量のリスト
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | Yes |
Changes observed during successful MCP inspections.
v0.5.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions returning a list of features but omits details like search behavior (exact or fuzzy match), performance, or authentication 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 very short but structured with Args and Returns sections in a Python docstring format. Every line provides useful information, though it could be slightly more verbose without losing conciseness.
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 simple search tool, the description covers the basic purpose and parameter. However, it lacks details on the return structure (list of what?), search algorithm, and edge cases. Given no output schema, it would benefit from explaining the result format.
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 schema has no description for the keyword parameter (0% coverage), but the description adds concrete examples ('人気', '距離', '騎手') that clarify expected usage. This adds significant meaning beyond the bare schema definition.
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 states it searches features by keyword, using a specific verb and resource. However, it does not explicitly distinguish itself from sibling tools like get_feature_by_category or get_important_features, which could cause confusion about when to use each.
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 guidance is provided on when to use this tool versus alternatives. The description does not include any context about use cases, prerequisites, or limitations, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.