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petropt/petro-mcp

calculate_coleman_critical

Calculate Coleman critical rate to assess liquid loading risk in low-pressure gas wells (wellhead pressure < 500 psi). Input pressure, temperature, gas gravity, tubing ID, and optional current rate to compare.

Instructions

Coleman et al. (1991) critical rate for liquid loading (20% below Turner).

Recommended for low-pressure gas wells (< ~500 psi wellhead pressure).

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). 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
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?

No annotations provided, so description is the sole source. It describes the calculation based on Coleman et al., which is a pure function. It does not cover any side effects, errors, or edge cases, but for a calculation tool this is acceptable.

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?

Two brief paragraphs: first states purpose and condition, second lists parameters efficiently. No fluff, all sentences earn their place.

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 5 parameters and an existing output schema, the description covers inputs well and provides usage context. It could mention the return value (critical rate) explicitly, but output schema likely covers it.

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 has no descriptions (0% coverage), so the description's Args section provides clear, concise explanations for all five parameters, adding meaning beyond type and title.

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 Coleman critical rate for liquid loading, specifically being 20% below Turner, and distinguishes it from its sibling calculate_turner_critical. The verb 'calculate' and the resource 'critical rate' are specific.

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?

Explicitly recommends use for low-pressure gas wells (<500 psi wellhead pressure), implying when to use it versus Turner. However, it could more directly say 'not for high pressure' or name the alternative explicitly.

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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