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

The description discloses the Newton-Raphson algorithm and the iterative nature, giving insight into how it works. It does not cover potential convergence issues, error conditions, or output format, but with no annotations provided, this is a reasonable amount of behavioral detail for a calculation 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 four sentences, front-loaded, and wastes no words. The final sentence about LLM reliability is somewhat extra but arguably useful for tool selection.

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?

The description lacks explicit guidance on which parameters to supply for each solveFor value, which is critical given 8 parameters and no output schema. The schema hints at omitting the solved variable, but does not clarify the full required input set for each scenario, leaving invocation ambiguous.

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 already covers parameter descriptions for 75% of the fields, and the description adds minimal extra parameter semantics. The description's examples map to the solveFor values but do not explain the dependencies between parameters (e.g., which inputs are required for each solveFor scenario).

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 identifies the tool as a 'reverse solver' that solves for an unknown variable (rate, term, residual, or PV) given a target payment. It clearly differentiates from sibling tools by specifying 'commercial equipment leases' and the reverse-solving nature.

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 usage context with example questions like 'what rate am I really paying?' and notes this tool handles iterative solving that LLMs cannot do reliably by hand. However, it does not explicitly contrast with forward calculators like calculate_lease or state when not to use them, so it falls short of a 5.

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