break_even

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

With no annotations, the description carries the full burden. It discloses the bisection method and the return values (required input, change from baseline, achieved metric, residual), which are useful behavioral traits. It does not mention potential failure modes (e.g., no solution exists) or state effects, but for a read-only solver this is adequate.

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?

A single, front-loaded sentence states the purpose, method, and return values without waste. It is well-structured and every clause adds meaningful 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?

With no output schema, the description does list the key return values, which is helpful. However, with 8 parameters and no explicit parameter explanations or success/failure conditions, the description is not fully complete for an agent to invoke the tool without additional inference.

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 only 38% (descriptions exist for inputs, horizon, template, but not for bounds, solve_for, target_value, period_label, target_metric). The description does not compensate: it only indirectly hints at solve_for and target_value via the purpose sentence, leaving bounds, inputs, and period_label unexplained.

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 uses a specific verb ('Solve for') with a clear resource ('input value') and goal ('make an output metric reach a target value'), which distinguishes it from sibling tools like sensitivity_analysis and run_scenario. The mention of 'bisection' further clarifies the numeric method. This is a clear, distinct purpose.

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 usage context is implied by the purpose: use this tool when you need to find the input value that achieves a target output metric. However, there is no explicit guidance on when not to use it or how it compares to alternatives like run_scenario or sensitivity_analysis.

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