list_store_credits

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 the underlying API endpoint (GET /v1/user_credits), and the complete return structure including all fields (total_found, returned, total_balance, credits[] with customer_id and balance). This is substantial behavioral context. It does not explicitly state that this is a read-only operation or mention rate limits, but for a listing tool with no mutation, this is adequate.

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-organized with clear sections (用途, API, 回傳結構). Every sentence adds value, and the information is presented in a scannable structure. It is neither too terse nor excessively verbose.

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?

The description is highly complete for a list tool: it states the purpose, use cases, underlying API, and detailed output structure. Since no output schema exists in the tool definition, this in-description return schema is essential. It lacks explicit pointers to sibling operations or pagination behavior, but remains sufficient for an agent to correctly select and invoke the tool.

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 single parameter max_results is fully described in the schema ('最多回傳筆數'), giving 100% coverage. The description adds context by explaining the response contains 'total_found' and 'returned', helping the agent understand the effect of max_results. It does not fully compensate for any ambiguity about 'all customers' vs. the maximum results limit, but the schema already handles the parameter.

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 opens with a clear verb+resource statement: '取得所有客戶的儲值金餘額列表' (get all customers' store credit balance list). It specifies the resource (store credit balances) and distinguishes this from sibling tools like update_customer_store_credits, which is a write operation. It also adds use cases, reinforcing specificity.

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 explicitly explains when to use the tool: '瀏覽客戶儲值金餘額概況' (browse overview), and gives concrete applications like calculating store credit liability ('計算儲值金負債') and identifying high-balance customers ('找出高餘額客戶'). However, it does not mention alternatives or when not to use it, so it stops short of a full 5.

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