verify_solution

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

With no annotations, the description carries the full burden. It explains the input formats and gives an example output ('verified: True'), but does not detail return structure (beyond the example), error behavior, or limitations. This is adequate but not rich.

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 concise, well-structured docstring with Args, Returns, and Examples sections. Every sentence adds value, and the example clarifies usage clearly. No redundancy.

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?

For a low-complexity tool, the description covers all parameters, gives an example, and mentions the return type. Although an output schema exists (not shown), the description's 'Returns: Verification result' plus example is sufficient for an agent to invoke the tool 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?

The schema provides only parameter names and types (0% description coverage). The description compensates fully by explaining each parameter: equation format ('lhs = rhs' or 'expr'), solution meaning, and variable default. This adds significant value beyond the schema.

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's function: 'Verify that a value satisfies an equation.' It uses the specific verb 'verify' and identifies the resource (a solution against an equation). This distinguishes it from sibling tools like verify_derivative, verify_integral, and verify_equality, which target different verification scenarios.

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 clear context for when to use the tool: when you have an equation and a claimed solution to check. It does not explicitly name alternatives or exclusions, but the context is sufficient to avoid obvious misuse.

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