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petropt

petropt/petro-mcp

calculate_price_sensitivity

Calculate net present value across multiple oil and gas price scenarios to generate sensitivity 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?

No annotations provided. Description describes inputs and function but does not disclose whether the tool has side effects, authorization requirements, or edge cases. It is a pure calculation, but that is implied rather than stated.

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?

Description is front-loaded with the core purpose and uses a clear Args format. Every sentence is necessary given the lack of schema descriptions. Could potentially be more concise but is well-structured.

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

Completeness3/5

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

Covers inputs comprehensively but does not describe output format despite the output schema existing. While the schema may specify types, the description could alert the agent to the return structure (e.g., list of NPV values). Adequate but not complete.

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 coverage is 0%, so description compensates by explaining each parameter in the Args block (e.g., 'monthly_oil_bbl: Monthly oil production (bbl) per period.'). This adds meaning beyond the schema's field names and types.

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?

Description clearly states 'Calculate NPV across multiple price scenarios for sensitivity/tornado charts.' This is a specific verb-resource pair and distinguishes from sibling tools like calculate_npv or calculate_breakeven_price.

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?

Implies use for sensitivity analysis via 'for sensitivity/tornado charts', but no explicit when-to-use, when-not-to-use, or alternatives. Among many economic tools, clearer guidance would help.

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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