gpu_solve

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

With no annotations, the description carries full burden but only mentions 'GPU fallback' without explaining behavior on GPU failure, performance implications, side effects, or whether results are symbolic or numeric.

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 concise sentence, but its brevity sacrifices necessary detail; it could include parameter semantics and usage 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 complexity of batched linear systems and zero schema coverage, the description is incomplete—it does not explain output format, error conditions, or when GPU fallback applies.

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 provides no explanation of the parameters 'a_batch' and 'b_batch' beyond their names, leaving the agent to infer from schema structure alone.

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 solves batched linear systems, with the specific verb 'Solve' and resource 'batched linear systems'. It distinguishes from siblings like 'solve' (likely symbolic) and 'lstsq' (least squares).

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 implies usage for batched linear systems but provides no explicit guidance on when to use this tool versus alternatives like 'solve' or 'lstsq', nor any prerequisites or exclusions.

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