Retrieve Japanese government statistical table metadata as CSV. Filter by keyword, field, year, or code to get the data you need.
統計表情報をCSVで取得する.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| gov_code | No | ||
| open_years | No | ||
| stats_code | No | ||
| search_word | No | ||
| stats_field | No | ||
| survey_years | No | ||
| updated_date | No | ||
| start_position | No | ||
| stats_name_list | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.4.0Input schema / additionalPropertiesAdded value: +falseDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds minimal context beyond stating the CSV format, with no mention of pagination, limits, rate limits, or any side effects. It does not contradict the annotations, but provides no additional behavioral insight.
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, efficient sentence with no excess wording or filler. It is front-loaded with the core action and format, making it easy to parse. However, its brevity borders on underspecification, though that is penalized in other dimensions.
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 complexity (10 optional parameters, no schema descriptions), this one-line description is severely incomplete. It fails to convey what the function does in detail, when to use it, or how to interpret parameters. The presence of an output schema mitigates return-value explanation, but the description still lacks essential context for correct invocation.
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 description coverage is 0%, meaning the schema has no descriptions for any of the 10 parameters. The description must compensate by explaining parameters or typical usage, but it says nothing about limit, gov_code, open_years, stats_code, or any other parameter. This is a critical gap that leaves the agent unable to understand parameter semantics.
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 specifies a clear verb (取得する 'retrieve'), resource (統計表情報 'statistics list information'), and format (CSV). It distinguishes from the sibling get_stats_list by explicitly noting the CSV output, though it doesn't elaborate on the nature of the statistics list or provide any parameter context. This is clear enough for basic identification.
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 gives no indication of when to use this tool versus alternatives such as get_stats_list or other CSV variants. There is no mention of conditions, exclusions, or recommendations, leaving the agent without guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.