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 for behavioral disclosure. It states what the tool computes but doesn't describe important behavioral aspects: whether this is a pure calculation (likely read-only), what format the output takes, whether arrays must be same length, handling of invalid inputs, or any computational constraints. The description is minimal beyond the core operation.

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 appropriately concise with three sentences: purpose statement, context explanation, and parameter definitions. Each sentence earns its place, though the structure could be slightly improved by front-loading the parameter section more clearly. There's no wasted text, making it efficient for an agent to parse.

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 tool has an output schema (which handles return values), no annotations, and only 2 parameters with good semantic explanation in the description, the description is minimally complete. However, for a computational tool with no behavioral context and many similar sibling tools, it should provide more guidance on usage context and limitations. The description covers the basics but leaves important contextual gaps.

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 meaning for both parameters: 'cumulative_production: Cumulative production values' and 'rate: Instantaneous production rates.' This explains what each parameter represents in the context of the material balance time calculation, adding significant value beyond the bare schema which only shows they are arrays of numbers.

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 tool's purpose: 'Compute material balance time: tMB = Np / q' with a specific mathematical operation. It further explains this is 'The Blasingame x-axis transform that converts variable-rate production into an equivalent constant-rate time for decline type curve matching.' This distinguishes it from many sibling tools focused on different calculations, though it doesn't explicitly differentiate from similar RTA tools like rta_blasingame or rta_flowing_material_balance.

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 explicit guidance on when to use this tool versus alternatives is provided. The description mentions 'decline type curve matching' which gives some context, but it doesn't specify prerequisites, when this calculation is appropriate, or what alternatives might exist among the many sibling RTA tools. The agent must infer usage from the purpose statement alone.

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