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petropt

petropt/petro-mcp

calculate_price_sensitivity

Calculate NPV across multiple oil and gas price scenarios to assess project sensitivity and generate tornado charts for investment decisions.

Instructions

Calculate NPV across multiple price scenarios for sensitivity/tornado charts.

Args: monthly_oil_bbl: Monthly oil production (bbl) per period. monthly_gas_mcf: Monthly gas production (Mcf) per period. monthly_water_bbl: Monthly water production (bbl) per period. opex_monthly: Monthly operating expense ($). capex: Total capital expenditure ($). price_scenarios: List of dicts with 'oil_price' and 'gas_price'. discount_rate: Annual discount rate. Default 0.10. royalty_pct: Royalty fraction (0-1). Default 0.125.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monthly_oil_bblYes
monthly_gas_mcfYes
monthly_water_bblYes
opex_monthlyYes
capexYes
price_scenariosYes
discount_rateNo
royalty_pctNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

As a calculation tool, it is assumed read-only, but the description does not explicitly confirm no side effects, lacking behavioral context beyond the function.

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

Conciseness5/5

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

Concise one-line summary followed by a well-structured Args list; no redundant information.

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

Completeness5/5

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

Given the output schema exists, the description adequately covers purpose, parameters, and usage context for a calculation tool.

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

Parameters5/5

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

With 0% schema description coverage, the description compensates fully by listing each parameter with a clear meaning (e.g., 'Monthly oil production (bbl) per period').

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 it calculates NPV across multiple price scenarios for sensitivity/tornado charts, with a specific verb and resource, distinguishing it from single-NPV siblings.

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?

Usage is implied through 'for sensitivity/tornado charts', but no explicit when-to-use or alternatives are mentioned, leaving room for ambiguity.

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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