get_product_reviews

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently explains the return format (a dict with 'reviews' list and 'count') and the effect of max_count (maximum number of reviews, range 1-100, default 20). This adds meaningful context beyond the name and schema, though it does not discuss potential errors, auth, or rate limits, which would elevate it further.

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 optimally concise and well-structured: a one-sentence summary, a clear return value explanation, and a two-line Args section. Every sentence is informative, with no filler or redundant 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?

For a simple read tool with two parameters and an existing output schema, the description is complete. It covers the return structure, parameter ranges, and source of the key input. The sibling tools are distinct, and nothing critical is missing 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?

Schema description coverage is 0%, so the description must fully compensate. It does: product_id is explained as 'the numeric product id (from search_products),' and max_count is given a range and default. This adds semantic meaning far beyond the type-only schema, clarifying how and why each parameter is used.

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 'Fetch customer reviews for a Tokopedia product.' This is a specific verb+resource that immediately distinguishes it from siblings like get_product_details and search_products. The scope (reviews, not details or search) is 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?

The description implies usage context by noting that product_id comes 'from search_products', suggesting a typical workflow. However, it does not explicitly state when to prefer this tool over siblings or provide exclusion criteria. The usage guidance is implicit rather than explicit, earning a mid-range score.

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