bellNumber

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 states what the tool does but lacks behavioral details: it doesn't disclose performance characteristics (e.g., time complexity for large n), error handling (e.g., for invalid inputs beyond the schema's integer range), or output format (e.g., integer result, potential overflow).

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 in Chinese that directly states the tool's function. It is front-loaded with no unnecessary words, making it highly concise and well-structured for its purpose.

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 complexity (mathematical computation with one parameter) and lack of annotations and output schema, the description is incomplete. It doesn't address key contextual aspects like computational limits, result interpretation, or error cases, which are important for an AI agent to use the tool effectively.

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 description adds minimal semantics: '第n个' implies 'n' is an index for the Bell number sequence. However, with 0% schema description coverage and no output schema, it doesn't explain valid ranges (e.g., non-negative integers typical for Bell numbers) or the meaning of the result. The baseline is 3 since the schema covers the parameter type and constraints, but the description doesn't fully compensate for the coverage gap.

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: '计算第n个贝尔数（集合划分数）' translates to 'calculate the nth Bell number (number of set partitions)'. This specifies the verb ('calculate') and resource ('nth Bell number'), though it doesn't explicitly differentiate from siblings like 'catalan' or 'fibonacci' beyond naming a different mathematical sequence.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, limitations (e.g., computational constraints for large n), or suggest other tools for related tasks (e.g., 'combination' for combinatorial calculations).

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