get_repurchase_analysis

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

No annotations are provided, so the description carries the full burden. It is transparent about the computed metrics, but does not explicitly state that it is a read-only operation, nor describe the output format or aggregation level. This does not contradict annotations (none exist), but it leaves some ambiguity about the nature of the analysis.

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: two short sentences that front-load the core function and list key metrics. Every word earns its place, with no filler or repetition.

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 simple two-parameter input and the explicit enumeration of output metrics in the description, the tool's behavior is mostly covered. The lack of an output schema is mitigated by listing exactly what is calculated. However, it does not describe the return format or edge cases (e.g., empty date ranges), which prevents a perfect score.

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 provides 100% coverage with descriptions for both parameters (start_date and end_date). The description adds no additional parameter context beyond what the schema already contains. Baseline 3 is appropriate since the schema handles parameter semantics adequately.

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 states a clear purpose: '分析客戶回購率與回購週期' (analyze customer repurchase rate and repurchase cycle), and lists specific metrics (新客 vs 舊客比例, 回購率, 平均回購天數). This clearly distinguishes it from sibling tools like get_rfm_analysis or get_customer_lifecycle, which focus on different customer analytics dimensions.

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 does not mention exclusions, prerequisites, or contrast with overlapping analysis tools such as get_rfm_analysis or get_customer_lifecycle. The only implied usage is for repurchase analysis, but explicit guidance is missing.

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