create_product_review

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

With no annotations, the description carries the full burden and discloses side effects: it adds a review to the list, may be immediately public or pending review based on store settings, and affects average rating. It also specifies the return structure. This is strong behavioral transparency, though it omits details like permission requirements or rate limits.

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 (purpose, API, return structure, side effects) and is appropriately concise. Every section earns its place, and the [WRITE] tag front-loads the key action. It avoids unnecessary fluff.

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 complete for a write operation with one param and no output schema, as it provides return structure and side effects. However, it could elaborate on validation rules or required fields within review_data, though the schema example helps. Overall, it provides enough context for an agent to invoke it 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 schema description covers 100% of the single parameter 'review_data', including an example with product_id, rating, content, and reviewer_name. The tool description itself does not add further parameter details, so it meets the baseline but does not exceed it. The example in the schema is the primary semantic source.

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 function with a specific verb ('建立' - create) and resource ('單筆商品評論' - single product review), distinguishing it from sibling tools like bulk_create_product_reviews and update_product_review. The [WRITE] tag and API endpoint further reinforce the purpose.

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 a clear usage context: '適用於客服代為補登評論或匯入歷史評論資料' (for customer service to add reviews on behalf or import historical review data). It does not explicitly mention alternatives or exclusions, but the singular nature and sibling tools imply when to use it. The guidance is sufficient but could be more explicit about bulk scenarios.

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