solve_linear

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

There are no annotations, and the description does not disclose the output format, return behavior, error handling, or any constraints (e.g., linearity, solution domain). This leaves the agent uncertain about what to expect from the tool.

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 concise, uses a clear structure, and includes an illustrative example without any redundant 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?

While the input format is well explained, the description does not mention the output shape or any expectations about the solution (e.g., unique solution, multiple solutions, no solution). Given the absence of an output schema, this omission reduces completeness.

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?

The schema provides no descriptions for the parameters, but the description explains the delimiters (';' for system, ',' for variables) and includes a concrete example, adding meaningful context that the schema lacks.

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 a system of equations and provides the exact input format with an example, making its purpose unambiguous.

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 explains how to format inputs but does not explicitly state when to use this tool over alternatives like solve_expression or simplify_expression. The name and sibling context imply it is for systems, but it lacks direct guidance.

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