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petropt

petropt/petro-mcp

calculate_gas_z

Calculate gas compressibility factor (Z) using Hall-Yarborough or Dranchuk-Abou Kassem correlations. Supports Sutton and Piper pseudocritical methods for sour gases and condensates.

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 provided, so description must cover behavioral traits. It mentions inputs and defaults but does not describe return value (output schema exists but not referenced), constraints, or error conditions. Adequate but not detailed.

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?

Brief summary followed by parameter list with clear formatting. Could be slightly shortened, but front-loaded and well-organized. Every sentence adds value.

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?

With output schema present, coverage of return value is not needed. Parameter descriptions are complete, including defaults and method choices. No mention of constraints or typical usage, but sufficient for a calculation tool.

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?

Adds meaning beyond schema by specifying units ('F', 'psi'), ranges (0-1 for fractions), and options for methods. Schema has 0% description coverage, so description compensates well.

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 gas Z-factor with choice of correlation and pseudocritical methods, specifying default methods. It is distinct from sibling tools which focus on other calculations.

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?

Provides explicit guidance on when to use each pseudocritical method (e.g., 'piper' better for gas condensates and sour gases). Lacks explicit when-not-to-use or alternatives among siblings, but the focused scope makes it clear.

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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