petropt/petro-mcp

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

No annotations are provided, so the description carries full burden for behavioral disclosure. While it explains the calculation logic, it doesn't cover important behavioral aspects: whether this is a read-only calculation or has side effects, what happens with invalid inputs (e.g., empty arrays, non-numeric values), performance characteristics, or error handling. For a calculation tool with no annotation coverage, this represents significant gaps.

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 appropriately concise and well-structured. It opens with the core purpose, explains the algorithm, then provides parameter semantics in a clear 'Args:' section. Every sentence adds value with no redundant information. The structure is logical and front-loaded with the most important 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?

Given that there's an output schema (which handles return values), no annotations, and only one parameter with good semantic coverage in the description, the description is adequate but has gaps. It explains what the tool calculates and the parameter meaning, but doesn't address behavioral aspects like error conditions or performance. For a financial calculation tool, this represents a minimum viable level of completeness.

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?

With 0% schema description coverage, the description must compensate, and it does so effectively. It explains the 'cash_flows' parameter's meaning ('Monthly cash flows ($)'), format ('array'), and provides crucial semantic context: 'First element is typically negative (capex).' This adds significant value beyond the bare schema, though it doesn't specify units or constraints beyond the typical first element.

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 purpose: 'Calculate payout period -- months to recover initial investment.' It specifies the verb ('calculate'), resource ('payout period'), and defines the concept. However, it doesn't explicitly differentiate from sibling tools like 'calculate_npv' or 'calculate_irr', which are also financial calculation tools in the same domain.

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 minimal usage guidance. It explains the algorithm ('Payout is the first month where cumulative cash flow >= 0') and notes that the first cash flow element is typically negative, but doesn't specify when to use this tool versus alternatives like 'calculate_npv' or 'calculate_irr' from the sibling list. No explicit when-not-to-use guidance or prerequisites are mentioned.

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