Sakila MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool performs analysis and returns percentage breakdowns, but doesn't describe output format, data freshness, rate limits, authentication needs, or potential side effects. For a tool with no annotations, this is a significant gap in transparency, as the agent lacks critical 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 concise and front-loaded, with two sentences that directly state the purpose and key capability. There's no wasted text or redundancy. However, it could be slightly more structured by explicitly listing the three customer types (new, active, dormant) for clarity, but it's still efficient.

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 of an analysis tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., a report, percentages, time-series data), how the analysis is computed, or any limitations. For a tool that likely returns structured data, this leaves the agent unprepared to interpret results effectively.

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 adds no parameter semantics beyond what the input schema provides. The schema has 100% coverage with a clear enum for 'period' (all_time, last_month, last_week) and a default. The description doesn't explain what these periods mean in the context of activity analysis or how they affect results. Since schema coverage is high, the baseline is 3, but no extra value is added.

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: '顧客アクティビティ分析を行います。新規・アクティブ・休眠顧客の割合を確認できます。' (Performs customer activity analysis. You can check the percentage of new, active, and dormant customers.) This specifies the verb ('analyzes') and resource ('customer activity'), and distinguishes it from siblings like get_customer_details (details) or get_customer_segments (segments). However, it doesn't explicitly differentiate from get_customer_rentals or get_top_customers, which might overlap in analyzing customer behavior, so it's not a perfect 5.

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. It doesn't mention prerequisites, context, or exclusions. For example, it doesn't clarify if this is for high-level summaries versus detailed breakdowns, or how it compares to get_customer_segments or get_top_customers. The lack of usage context leaves the agent guessing about appropriate scenarios.

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