petropt/petro-mcp

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions the tool calculates NPV for sensitivity charts but doesn't disclose output format, whether it's read-only or mutating, error conditions, computational complexity, or any assumptions about the model (e.g., time periods, tax implications). The description is functional but lacks operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with a purpose statement followed by parameter details. Every sentence earns its place: the first sentence defines the tool's function, and the Args section efficiently documents parameters. It could be slightly more front-loaded with key behavioral notes, but it's appropriately sized and avoids redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (8 parameters, economic modeling) and presence of an output schema (which handles return values), the description is moderately complete. It explains parameters well but lacks behavioral context (no annotations) and usage guidelines. For a tool with significant computational and domain complexity, more guidance on assumptions and limitations would be beneficial.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It provides clear semantic explanations for all 8 parameters in the Args section, defining units (bbl, Mcf, $), ranges (0-1 for royalty_pct), and structure (list of dicts for price_scenarios). This adds substantial value beyond the bare schema, though it doesn't explain array lengths or interdependencies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific purpose: 'Calculate NPV across multiple price scenarios for sensitivity/tornado charts.' It includes the verb 'calculate' and specifies the resource (NPV) and context (price scenarios for sensitivity analysis), distinguishing it from sibling tools like calculate_npv which likely calculates single-scenario NPV.

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

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

No guidance is provided on when to use this tool versus alternatives. While the purpose implies it's for sensitivity analysis, there's no mention of when to choose it over other economic tools like calculate_breakeven_price or calculate_well_economics, nor any prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.