solve_linear

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It mentions the constraint 'Max n=32' and input alternatives, but does not state what the tool returns (e.g., the solution vector) or how it handles singular or ill-conditioned systems. The description focuses on when to use it rather than what it does behaviorally.

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 extremely concise—three short lines covering usage, parameters, and an example. Every sentence adds value, no fluff or repetition. It is well-structured with clear labels ('When', 'Params', 'Example').

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 tool's simplicity and the existence of an output schema (which handles return values), the description adequately covers the key aspects: usage scope, parameter forms, constraints, and differentiation from siblings. The only gaps are edge-case behaviors like singular systems, which are not typically necessary for basic use.

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 has no parameter descriptions (0% coverage), but the description compensates well by explaining that 'A' is an n×n matrix, 'b' is length n, and 'coefficients' is an augmented n×(n+1) matrix. It also clarifies the mutually exclusive usage of A/b vs coefficients. The example further illustrates the parameter format.

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 explicitly states 'square linear system Ax=b' which clearly defines the tool's purpose as solving linear systems. It also distinguishes from polynomial roots and f(x)=0, effectively separating it from sibling tools like solve_polynomial and solve_root.

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 provides explicit usage context with 'When: square linear system Ax=b' and explicitly excludes 'polynomial roots or f(x)=0'. This helps the agent decide when to use this tool over alternatives. It also clarifies the two input formats (A/b or augmented matrix), giving additional guidance.

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