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 of behavioral disclosure. It provides the mathematical formula and parameter definitions, which helps understand what the tool does. However, it doesn't mention important behavioral aspects like units of the output, numerical precision, error handling for invalid inputs, or whether this is a pure calculation with no side effects. The formula reference (Lee, 1982) adds some context but doesn't fully describe tool behavior.

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 perfectly structured and concise. It starts with the purpose statement, provides the exact formula with citation, then lists all parameters with clear definitions. Every sentence earns its place - no redundant information, no unnecessary elaboration. The Args section is well-organized and easy 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's complexity (mathematical calculation with 5 parameters), no annotations, but with an output schema present, the description is mostly complete. It thoroughly documents all input parameters and the calculation formula. The presence of an output schema means the description doesn't need to explain return values. However, it could benefit from mentioning typical use cases or limitations of the Lee (1982) formula.

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?

With 0% schema description coverage (titles only provide parameter names), the description fully compensates by providing detailed semantic information for all 5 parameters. Each parameter gets: physical meaning (e.g., 'Formation permeability'), units (e.g., 'millidarcies'), and constraints where applicable (e.g., 'Porosity (fraction, 0-1)'). This adds substantial value beyond the bare schema.

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: 'Calculate radius of investigation for a well test.' It specifies the exact mathematical formula (Lee, 1982) and distinguishes this from sibling tools by focusing on a specific reservoir engineering calculation. The description goes beyond just restating the name to explain what the calculation represents.

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 provides no guidance on when to use this tool versus alternatives. While it's clear this calculates radius of investigation, there's no mention of when this specific calculation is needed, what scenarios it applies to, or how it differs from the many other reservoir engineering calculation tools in the sibling list. The agent must infer usage context from the tool name alone.

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