matrix_subtract

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

No annotations are provided, so the description carries full burden. It only states the calculation without disclosing behavioral traits like input validation (e.g., matrix dimensions must match), error handling, performance considerations, or output format. This is inadequate for a mutation-like operation with zero annotation coverage.

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 with no wasted words. It's appropriately sized for a simple mathematical operation and front-loaded with the core purpose, though it lacks detail.

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 (matrix operation with potential dimension constraints), no annotations, no output schema, and 0% schema coverage, the description is incomplete. It doesn't address key aspects like input validation, error cases, or return values, making it insufficient for reliable tool invocation.

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%, and the description doesn't add any parameter semantics beyond the names 'matrix_a' and 'matrix_b'. It doesn't explain what these parameters represent (e.g., 2D arrays), their expected formats, or constraints like size compatibility. With 2 undocumented parameters, the description fails to compensate for the schema 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 '计算两个矩阵的差' (calculates the difference between two matrices) states the verb and resource clearly, but it's vague about what 'difference' means mathematically (element-wise subtraction) and doesn't distinguish from sibling tools like 'matrix_add' or 'subtract'. It provides basic purpose but lacks specificity.

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 on when to use this tool versus alternatives like 'matrix_add' or general 'subtract'. The description implies usage for matrix operations but doesn't specify context, prerequisites, or exclusions, leaving the agent to infer based on tool name alone.

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