petropt/petro-mcp

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

With no annotations provided, the description carries the full burden. It discloses that the tool performs a 'discounted cash flow analysis' and returns specific financial metrics, which implies a computational, non-destructive operation. However, it lacks details on behavioral traits such as error handling, performance characteristics, or any side effects (e.g., data persistence or external calls), leaving gaps in transparency for an agent.

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?

The description is well-structured with a clear purpose statement, input explanation, and output listing, all in a compact format. Every sentence earns its place by providing essential information. It could be slightly more front-loaded by moving the output details earlier, but overall it is efficient 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 (12 parameters, economic analysis) and no annotations, the description does a good job explaining inputs and outputs. Since an output schema exists, it need not detail return values, but it still lists key metrics (NPV, IRR, etc.). The main gap is lack of behavioral context (e.g., computational limits), but it compensates well with parameter semantics and purpose clarity.

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?

The schema description coverage is 0%, so the description must compensate fully. It provides detailed semantics for all 12 parameters, including units (e.g., bbl, Mcf, $), ranges (e.g., 0-1 for fractions), defaults, and their roles in the analysis (e.g., 'applied at time 0' for capex). This adds significant meaning beyond the bare schema, effectively documenting each parameter.

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 action ('Full discounted cash flow analysis for a well') and distinguishes it from siblings by focusing on comprehensive economic metrics (NPV, IRR, payout period, etc.) rather than single calculations like 'calculate_npv' or 'calculate_irr' in the sibling list. It specifies the verb ('analysis') and resource ('a well') precisely.

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?

The description implies usage by mentioning it 'Takes production arrays (from decline forecast) plus economic assumptions,' suggesting it should be used after production forecasting. However, it does not explicitly state when to use this tool versus alternatives like 'calculate_npv' or 'calculate_irr' from the sibling list, nor does it provide exclusions or prerequisites beyond the implied input data.

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