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petropt

petropt/petro-mcp

calculate_turner_critical

Calculates minimum gas velocity and flow rate needed to continuously lift liquids from a gas well using the Turner droplet model.

Instructions

Turner et al. (1969) critical rate for gas well liquid unloading.

Calculates the minimum gas velocity and flow rate needed to continuously lift liquids from a gas well using the droplet model.

Args: wellhead_pressure_psi: Wellhead flowing pressure in psi. wellhead_temp_f: Wellhead temperature in degrees F. gas_sg: Gas specific gravity (air = 1.0). condensate_sg: Condensate specific gravity (optional). water_sg: Water specific gravity. Default 1.07. tubing_id_in: Tubing inner diameter in inches. Default 2.441. current_rate_mcfd: Current gas rate in Mcf/d for status check (optional).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
wellhead_pressure_psiYes
wellhead_temp_fYes
gas_sgYes
condensate_sgNo
water_sgNo
tubing_id_inNo
current_rate_mcfdNo

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 carries the burden. It states what is calculated but does not disclose possible error conditions, input validation, or limitations of the Turner model. Minimal behavioral detail beyond the calculation purpose.

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 structured with a clear formula name and parameter list. It is not overly verbose, but the parameter section could be more streamlined. Front-loads the key purpose effectively.

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?

Given an output schema exists, the description need not explain returns. However, for a specialized engineering tool, it lacks details like the Turner model's assumptions or range of applicability. Adequate but not fully complete for an agent to use confidently.

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 the description must compensate. It lists each parameter with a brief description (e.g., 'Wellhead flowing pressure in psi') and indicates defaults. This adds meaningful context beyond the schema titles, though not exhaustive.

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 Turner et al. (1969) critical rate for gas well liquid unloading, specifying the droplet model and minimum gas velocity and flow rate. This distinguishes it from siblings like calculate_coleman_critical.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives like calculate_coleman_critical, nor any context about prerequisites or scenarios. The description lacks 'when to use' and 'when not to use' information.

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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