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petropt

petropt/petro-mcp

calculate_gas_z

Calculate gas Z-factor using Hall-Yarborough or Dranchuk-Abou-Kassem correlation with Sutton or Piper pseudocritical method for sour gases.

Instructions

Calculate gas Z-factor with choice of correlation and pseudocritical method.

Z-factor methods: 'hall_yarborough' (default), 'dranchuk_abou_kassem'. Pseudocritical methods: 'sutton' (default), 'piper' (better for gas condensates and sour gases).

Args: temperature: Temperature in F. pressure: Pressure in psi. gas_sg: Gas specific gravity (air = 1.0). method: Z-factor correlation -- 'hall_yarborough' or 'dranchuk_abou_kassem'. pseudocritical_method: Pseudocritical method -- 'sutton' or 'piper'. h2s_fraction: Mole fraction of H2S (for Piper method, 0-1). co2_fraction: Mole fraction of CO2 (for Piper method, 0-1). n2_fraction: Mole fraction of N2 (for Piper method, 0-1).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
temperatureYes
pressureYes
gas_sgYes
methodNohall_yarborough
pseudocritical_methodNosutton
h2s_fractionNo
co2_fractionNo
n2_fractionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It details inputs but does not describe outputs, side effects, or behavioral traits like idempotency. Given the presence of an output schema, some behavioral info is inferred but not 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?

The description is clear and structured but the second paragraph is essentially an argument list that could be more concise. Overall it is efficient with no unnecessary text.

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 presence of an output schema, return values need not be explained. The description covers all 8 parameters with units and defaults, but lacks behavioral context like the tool's purpose in gas calculations. Still fairly complete 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?

The input schema has 0% description coverage, so the description adds critical meaning by explaining temperature units, pressure units, gas specific gravity, and the options for method and pseudocritical_method with usage notes.

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 the gas Z-factor with specified correlation and pseudocritical methods. It lists all parameters and defaults, distinguishing it from other 'calculate_*' tools like calculate_pvt_properties.

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

Usage Guidelines4/5

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

It provides guidance on when to use the Piper pseudocritical method for gas condensates and sour gases, but does not explicitly state when not to use this tool or suggest alternatives.

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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