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

No annotations are supplied, so the description carries the behavioral disclosure burden. It does convey a pure modeling/computation action and lists the output domains, but it omits return format, modeling assumptions, and how the individual computations relate to each other. This is adequate but not fully transparent.

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 single dense sentence with no filler and the main action is front-loaded. The jargon-heavy phrase 'unallocated option pool shuffle dilution waterfall' is somewhat unwieldy, but the description remains efficient and informative.

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?

There is no output schema, and the tool is a complex eight-parameter model, yet the description does not state the result format or the assumptions behind the dilution waterfall. Inputs are well documented, and the outputs are named, but the agent is left to infer the output contract.

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 input schema already provides 100% coverage with descriptions, units, and defaults for all eight parameters, so the baseline is 3. The description adds no additional parameter-level detail or relationships beyond what the schema contains, but none is strictly required.

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 ('Model') and enumerates four distinct outputs: net burn rate, cash runway zero-cash date, Post-Money SAFE cap dilution, and Series A option pool dilution waterfall. This clearly differentiates it from sibling tools like black_scholes or home_loan_emi, which address entirely different domains.

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 intended context is implied through startup-specific terms like cash runway, SAFE, and Series A, but there is no explicit statement of when to use this tool versus an alternative. No exclusions or when-not-to-use conditions are provided, so the agent must infer usage from domain cues.

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