generate_random_numbers

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

No annotations are provided, so the description carries full burden. It mentions '推荐' (recommendations), implying advisory output, but lacks details on behavioral traits such as whether results are deterministic, if there are rate limits, or how randomness is seeded. For a tool with no annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence with zero waste. It's front-loaded and appropriately sized for the tool's complexity, making it easy to parse without unnecessary elaboration.

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 the tool's low complexity (2 parameters, 100% schema coverage, no output schema), the description is minimally adequate. It states the purpose but lacks context on usage, behavioral details, or output format. Without annotations or output schema, more completeness would be beneficial, but it meets a basic threshold.

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 coverage is 100%, with clear descriptions for both parameters (lottery_type and count). The description adds no additional meaning beyond the schema, such as explaining how lottery_type affects number generation or what '组数' (groups) entails. Baseline 3 is appropriate as 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 tool's purpose as '生成随机彩票号码推荐' (generate random lottery number recommendations), which specifies the verb (generate) and resource (lottery numbers). It distinguishes from siblings like analyze_numbers or predict_lottery by focusing on random generation rather than analysis or prediction, though it doesn't explicitly name these alternatives.

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 no guidance on when to use this tool versus alternatives. It doesn't mention scenarios where random generation is appropriate (e.g., for quick picks, entertainment) or when to prefer sibling tools like analyze_numbers for data-driven insights or predict_lottery for forecasts.

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