list_product_reviews

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

With no annotations, the description properly carries the burden by disclosing the API endpoint (GET /v1/product_review_comments), the return structure (dict with total_found, returned, reviews[]), and per-review fields (id, product_id, product_name, rating, content, created_at). It also notes that content is a summary and product_name defaults to Chinese, adding useful behavioral context. It doesn't explicitly state pagination or rate limits, but the provided details are solid.

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 clear sections for purpose, usage, API, and return structure. Each sentence delivers useful information without redundancy or fluff, making it appropriately sized and easy to scan.

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 tool is simple (1 optional parameter, no output schema), and the description covers all essential aspects: purpose, usage alternative, API endpoint, and detailed return structure. It is complete enough for an agent to invoke correctly without needing further elaboration.

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?

Schema already fully describes the only parameter (max_results with default 50 and Chinese description). The tool description does not add extra semantics beyond what the schema provides, so the baseline of 3 applies; the schema covers 100% of parameter documentation.

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 uses a specific verb '取得' (get/list) and resource '商品評價列表' (product review list), clearly stating it lists product review summaries. It also distinguishes itself from get_product_review_detail by noting the sibling handles full review content, making the purpose unambiguous.

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?

Provides explicit use cases: monitoring review quality, finding low-rated products, tracking recent comments. It also directly names the alternative tool (get_product_review_detail) for full content with images and merchant replies, making when-to-use and when-not-to-use crystal clear.

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