get_customer_satisfaction_stats

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

No annotations are provided, so the description must cover behavioral aspects. It states that results are daily and include participation and average score, which is useful. However, it does not mention pagination, default date range handling, empty-parameter behavior, or any error conditions. For a read-only stats tool, this is adequate but not comprehensive.

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 concise and front-loaded with the main purpose. It has a slight redundancy between the first line and the second paragraph, but overall it is efficient and structured with parameter explanations. No fluff, and it uses bullets for parameters for clarity.

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?

An output schema exists (not shown), so return values need not be detailed. However, the description does not mention any limits, pagination, or behavior when no data matches. It gives examples for parameters but not edge cases. For a moderately simple stats tool, it is adequate but could be more complete regarding default behavior and result interpretation.

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 zero descriptions for parameters, so the description effectively compensates. It explains date_from/date_to as the survey date range with example format, and day_of_week as a filter with example values. This adds meaningful semantics beyond the bare schema, though it does not clarify optionality or behavior when fields are empty, but the examples are helpful.

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 explicitly states the purpose: providing daily customer satisfaction statistics from the railroad customer center, including participation count and average score. The verb '조회' (inquiry) and specific resource are clear, and the tool is unique among siblings, so no confusion with alternatives.

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 domain context (railroad customer center satisfaction survey) but does not explicitly state when to use this tool versus others. There are no direct sibling tools for customer satisfaction, but it lacks explicit guidance on usage scenarios or exclusions. The context is clear enough for an agent to infer, but not explicitly stated.

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