Retrieve features by category from JRA-VAN horse racing data. Specify a category like past performance, aptitude, or pedigree to get a list of relevant features for analysis.
カテゴリ別に特徴量を取得
Args:
category: カテゴリ名（過去成績、適性、人的要因、血統など）
Returns:
該当カテゴリの特徴量リスト
| Name | Required | Description | Default |
|---|---|---|---|
| category | 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 present, and the description only implies a read operation ('get') without confirming safety, auth requirements, or disclosing any behavioral traits. The agent must infer behavior from the tool name alone.
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 extremely concise, using a single line for purpose and structured parameter/return sections. No superfluous text—every word is necessary.
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 tool with one parameter and no output schema, the description covers the essential information. However, it lacks context about edge cases, limitations, or how the returned list is ordered, which could be important for practical use.
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 0% description coverage, but the description lists example category values ('past performance, aptitude, human factors, pedigree') which adds meaningful context beyond the schema's generic string type. However, it does not enumerate all allowed values or specify format.
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 states the tool gets features by category, specifying a parameter and return type. However, it does not distinguish from sibling tools like 'get_important_features' or 'search_features', leaving ambiguity about when to use this specific tool.
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, nor any conditions or exclusions. The agent receives no help in choosing among feature-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.