matrix_trace

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

With no annotations provided, the description carries full burden but only states what the tool does without behavioral details. It doesn't disclose error conditions (e.g., non-square matrices), computational complexity, or output format. The description is minimal and lacks transparency about how the tool behaves beyond its basic function.

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 purpose with zero wasted words. It's appropriately sized for a simple mathematical operation and front-loaded with the essential information.

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 mathematical tool with 1 parameter, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't address input constraints (square matrix requirement), error handling, or return value format, leaving significant gaps for an AI agent to understand proper usage.

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 but adds no parameter information. It doesn't explain that 'matrix' must be a square 2D array, specify element types, or provide examples. The description fails to add meaning beyond the bare schema.

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 verb '计算' (calculate) and the resource '方阵的迹' (trace of a square matrix), providing a specific mathematical operation. It distinguishes from siblings like matrix_determinant or matrix_inverse by focusing on trace calculation, though it doesn't explicitly contrast with them.

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 doesn't mention prerequisites (e.g., input must be a square matrix), when not to use it, or refer to sibling tools like matrix_determinant for different matrix operations.

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