get_stats_list_csv

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

With no annotations provided, the description carries the full burden of behavioral disclosure but provides almost none. It doesn't indicate whether this is a read-only operation, what permissions might be required, whether it has rate limits, what happens with the 10 parameters, or how results are returned. The single sentence only describes the basic function without any operational context.

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 - a single Japanese sentence that directly states the tool's core function. There's no wasted language or unnecessary elaboration. While this conciseness comes at the cost of completeness, the structure is efficient and front-loaded with the essential information.

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 parameters, no annotations, multiple similar siblings) and the presence of an output schema, the description is insufficient. While the output schema might describe return values, the description doesn't address the tool's behavioral characteristics, parameter meanings, or differentiation from alternatives. For a tool with this many parameters and sibling tools, more context is needed.

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 description provides zero information about any of the 10 parameters. With 0% schema description coverage and no parameter information in the description, an AI agent would have no semantic understanding of what search_word, survey_years, stats_field, or any other parameters mean or how they should be used. This is particularly problematic given the large number of parameters.

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 the tool's purpose: retrieving statistical table information in CSV format. It specifies both the action ('取得する' - get/retrieve) and the resource ('統計表情報' - statistical table information), with the output format ('CSVで') as a key differentiator. However, it doesn't explicitly distinguish this tool from sibling CSV tools like get_data_catalog_csv or get_meta_info_csv.

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 provides no guidance on when to use this tool versus alternatives. With multiple CSV-related siblings (get_data_catalog_csv, get_meta_info_csv, get_stats_data_csv) and similar non-CSV tools (get_stats_list), there's no indication of what makes this tool distinct or when it should be preferred over other options. The description is purely functional without contextual guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.