np_matmul

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

The description does not disclose any behavioral traits beyond the basic operation. No annotations are present, so the description carries the full burden. It fails to mention that both inputs must be 2D or the implications of dimension mismatches.

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 sentence with no wasted words, and the key information is front-loaded. However, it could be slightly expanded to include more context without becoming verbose.

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 simplicity of the tool and the presence of an output schema, the description is too minimal. It does not explain the return value, shape requirements, or how it handles broadcasting, which are important for an AI agent to use correctly.

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?

Since schema description coverage is 100% (both parameters have descriptions), the description of the tool itself adds no extra meaning. The schema already describes 'a' and 'b' as 'First input array (2D)' and 'Second input array (2D)', so the description provides no additional parameter semantics.

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 'Matrix product of two arrays,' which uses a specific verb ('product') and resource ('two arrays'). This distinguishes it from sibling tools like np_dot (dot product) and np_multiply (element-wise), as matmul is specifically for matrix multiplication.

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 such as np_dot or np_multiply. There is no mention of prerequisites, shape requirements, or when not to use it.

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