thong_ke

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns counts based on parameters, implying a read-only operation. However, it does not mention potential errors, rate limits, or what happens with invalid inputs, leaving some opacity.

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 extremely concise: one line for the main purpose followed by bullet-pointed examples. It front-loads the core action and wastes no words, making it easy for an agent to parse quickly.

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?

Given no output schema and low schema coverage, the description covers the main functionality but lacks details on return format, error handling, or boundary conditions. While adequate for simple counting, it leaves gaps for an agent to infer.

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 compensates by explaining parameters through examples. It defines 'loai' values (tong_quan, dieu_luat, ban_an) and 'nhom_theo' options for specific types. This adds significant meaning, though not all possible values are enumerated.

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 purpose: counting/statistics on data ('Đếm/thống kê số lượng trong kho dữ liệu'). It distinguishes from sibling tools like 'liet_ke_an_le' (listing) by focusing on aggregation, and the examples clarify the exact operations.

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 explicit usage patterns with parameter combinations (e.g., loai='tong_quan', loai='dieu_luat' with nhom_theo). This helps the agent decide when to use the tool, though it lacks explicit 'when not to use' or alternative tool references.

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