list_promotions

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

With no annotations provided, the description carries the burden of behavioral disclosure. It transparently reveals the API endpoint (GET /v1/promotions) and the return structure (dict with total_found, returned, items[] and item fields), which is valuable behavioral context beyond the schema. It does not mention pagination, authentication, or error behavior, but it goes well beyond a minimal description.

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 information—use cases, endpoint, and return structure—without redundancy or filler. The main purpose is front-loaded in the first line.

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?

For a simple list tool with no annotations and no output schema, the description is fairly complete: it provides the endpoint, return shape, and common fields, plus use-case context. It could be enhanced by explicitly explaining pagination semantics or naming complementary tools like search_promotions or get_promotion_detail, but it is adequate for an agent to select and invoke correctly.

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 input schema already provides 100% parameter description coverage for status and max_results. The description adds little beyond '支援依狀態篩選' and the return field list; it does not enrich the parameter semantics meaningfully. Baseline 3 is appropriate because the schema does the heavy lifting.

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 core function ('取得促銷活動列表') and adds the status-filter capability, making the purpose specific to listing promotions. It implies a distinction from detail/analysis tools by mentioning using promotion_id for further detail, but it does not explicitly contrast with sibling search_promotions, so it stops short of a 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 '用途' section gives clear context: browse all promotions, analyze promotion strategy, or retrieve a promotion_id for later detail queries. This indicates when to use the tool, though it does not explicitly state when not to use it or name alternative tools, so it lacks full exclusion guidance.

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