Get example values from a specified column to understand the data format and content for JRA-VAN horse racing analyses.
特定カラムの値の例を取得（データ形式理解用）
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| table_name | Yes | ||
| column_name | 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 responsibility. It only states 'get examples' without disclosing behavioral traits like the effect of the limit parameter, ordering of results, required permissions, or the response format. This is insufficient for a data retrieval 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?
The description is a single sentence with no redundancy. Every word contributes meaning, making it appropriately sized and front-loaded.
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?
Given the tool's simplicity (3 parameters, no output schema), the description covers the basic purpose but omits important details like the limit parameter's role and the return format. It is missing nuanced context that would fully guide an agent.
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 input schema has 3 parameters with titles but no descriptions (0% coverage). The description does not elaborate on any parameter, adding no semantic value beyond the schema. While parameter names are self-explanatory, the description fails to compensate for the lack of schema descriptions.
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 retrieves examples of column values for understanding data format. The verb 'get' and resource 'column value examples' are specific. It distinguishes from sibling tools like get_table_sample_data which retrieve multiple rows/columns.
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 description includes a use case ('for understanding data format') but does not provide explicit guidance on when to use this tool versus alternatives such as get_table_sample_data or get_database_schema. No exclusions or when-not-to-use criteria are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.