solve_linear

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

No annotations provided; description only states the operation without disclosing behavior for singular systems, error handling, or method implications. Minimal behavioral insight.

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?

Single sentence is concise but omits valuable context. Could include brief parameter hints without sacrificing brevity.

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?

With 0% schema coverage, no annotations, and a minimal description, the tool definition lacks completeness for a mathematical operation that has common pitfalls (singularity, dimension mismatch).

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 adds no information about parameters a, b, or method. Parameters are entirely undocumented beyond schema types.

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?

Description uses specific verb 'solve' and resource 'square linear system Ax = b', clearly indicating the tool's purpose. It differentiates from sibling tools like 'solve' or 'lstsq' by specifying the square system requirement.

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 (e.g., lstsq for non-square systems). Missing context for prerequisites like matrix invertibility.

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