mode

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe how it handles edge cases (e.g., multiple modes, empty arrays, non-numeric elements), what format the output takes, or whether it modifies input data. For a statistical tool with zero annotation coverage, this leaves significant behavioral gaps.

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 that states the core purpose without unnecessary words. It's appropriately sized for a simple mathematical function and front-loads the essential information. Every word earns its place in conveying the tool's function.

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 statistical calculation tool with no annotations, no output schema, and 0% parameter documentation, the description is incomplete. It doesn't address output format, error handling, mathematical assumptions, or common usage patterns. While concise, it lacks the contextual information needed for reliable tool invocation in various scenarios.

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 compensate for undocumented parameters. It mentions '数组' (array) which maps to the 'numbers' parameter, but doesn't specify expected element types (numbers only? mixed types?), array size constraints, or handling of invalid inputs. With 1 parameter at 0% coverage, the description adds minimal semantic value beyond the parameter name.

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 specific mathematical operation ('计算数组的众数') with the exact resource ('数组'), distinguishing it from sibling tools like 'mean', 'median', 'max', and 'min' that perform different statistical calculations. It uses precise terminology that leaves no ambiguity about the tool's function.

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 like 'mean', 'median', 'max', or 'min'. It doesn't mention typical use cases for mode calculation (e.g., finding most frequent values in datasets) or any prerequisites. The agent must infer usage from the mathematical definition alone.

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