karte-datahub-mcp

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: automatic date constraints with defaults, parameter defaults, and limit range (1-10000). However, it doesn't mention important aspects like whether this is a read-only operation, potential rate limits, authentication requirements, or what happens with large result sets beyond the limit parameter. The description adds useful context but leaves significant gaps.

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 well-structured with a clear purpose statement followed by detailed parameter documentation. It's appropriately sized for a 6-parameter tool. The only minor improvement would be front-loading more critical behavioral information before the parameter details, but overall it's efficient with minimal waste.

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 complexity (6 parameters, no annotations, but with output schema), the description is quite complete. It thoroughly documents all parameters and their semantics. The presence of an output schema means the description doesn't need to explain return values. The main gap is lack of behavioral context around permissions, rate limits, or error conditions, but the parameter documentation is comprehensive.

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 description coverage is 0%, so the description must fully compensate. It does this excellently by providing detailed parameter documentation in the Args section: each parameter's purpose, format examples (YYYYMMDD, 'event_name = "click"'), default values, constraints (limit 1-10000), and special cases (None for no limit). This adds substantial meaning beyond what the bare schema provides.

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: 'KARTEイベントデータを取得する' (retrieve KARTE event data). It specifies the verb (retrieve) and resource (KARTE event data). However, it doesn't explicitly differentiate from sibling tools like count_karte_events or execute_karte_sql, which prevents a perfect score.

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 some usage context by mentioning automatic date constraints (default: 2 days ago to yesterday), which helps understand when to use it for date-filtered queries. However, it doesn't explicitly state when to use this tool versus alternatives like count_karte_events (for counting) or execute_karte_sql (for custom SQL), leaving the guidelines somewhat implied rather than explicit.

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