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petropt

petropt/petro-mcp

fit_ple_decline

Fit a Power Law Exponential decline model to production data to analyze transient and boundary-dominated flow regimes in tight or shale reservoirs.

Instructions

Fit Power Law Exponential (PLE) decline model to production data.

The PLE model (Ilk et al., 2008) captures transient and boundary-dominated flow regimes in tight/shale reservoirs. Uses petbox-dca for the forward model.

Args: production_data: List of dicts with 'time' (months) and 'rate' keys, or 'oil'/'gas' keys (time assumed as sequential months).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
production_dataYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It mentions the use of petbox-dca for the forward model but does not disclose whether the tool is read-only, has side effects, or requires specific permissions. Error handling or convergence behavior is omitted.

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 concise with a clear two-sentence purpose statement and a separate args section. It avoids unnecessary details but could integrate the args more naturally. Overall, every sentence serves a purpose.

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?

With an output schema present, the description need not explain return values, but it still lacks usage guidelines and behavioral transparency. The parameter documentation is good, but overall completeness is adequate but not thorough.

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?

The description adds significant detail to the lone parameter production_data, specifying accepted key formats ('time'/'rate' or 'oil'/'gas') and assumptions about time units (sequential months). This goes beyond the schema's minimal structure (array of objects).

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 fits a Power Law Exponential decline model to production data. It names the specific model, cites a reference, and distinguishes from sibling tools like fit_decline, fit_duong_decline, and fit_sepd_decline.

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?

The description implies usage for tight/shale reservoirs capturing transient and boundary-dominated flow, but lacks explicit guidance on when to use this tool versus other decline models. No when-not or alternative recommendations are provided.

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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