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petropt

petropt/petro-mcp

calculate_breakeven_price

Determines the minimum oil price required for net present value to equal zero, using bisection method to find breakeven price given production, costs, and discount rate.

Instructions

Calculate breakeven oil price -- minimum price for NPV = 0.

Uses bisection to find the oil price at which discounted net cash flow equals zero.

Args: monthly_production_bbl: Monthly oil production (bbl) per period. monthly_opex: Monthly operating expense ($). capex: Total capital expenditure ($). discount_rate: Annual discount rate. Default 0.10. royalty_pct: Royalty fraction (0-1). Default 0.125. months: Number of months to evaluate (default: length of production array).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monthly_production_bblYes
monthly_opexYes
capexYes
discount_rateNo
royalty_pctNo
monthsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description reveals the bisection algorithm and that it finds the price where discounted net cash flow equals zero. However, it does not disclose convergence behavior, error handling, or what happens if no solution exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise: one sentence for the main purpose, one sentence for the method, and a bulleted list of arguments. Every sentence earns its place, though the method detail could be merged.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema (present but not shown), the description covers the tool's purpose, parameters, and underlying algorithm. It is adequate for an agent to use the tool correctly, though it omits edge cases and assumptions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description provides brief explanations for each parameter (e.g., monthly_production_bbl as 'Monthly oil production (bbl) per period') and notes defaults. This adds meaningful context beyond the schema's empty descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool calculates the breakeven oil price, defined as the minimum price for NPV=0. This is a specific verb+resource combination that distinguishes it from sibling tools like calculate_npv or calculate_price_sensitivity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a breakeven price is needed, but does not provide explicit when-to-use, when-not-to-use, or alternative tools. No guidance on exclusions or prerequisites.

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

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