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 describes what properties are returned and lists correlation options, but doesn't mention computational characteristics (e.g., performance, accuracy limitations), error handling, or whether this is a read-only calculation versus a state-changing operation. It provides basic behavioral context but lacks depth.

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 and efficient: purpose statement first, followed by return values, correlation options, then parameter explanations. Every sentence adds value, with no redundant information. The formatting of correlation sets and parameter descriptions enhances readability without unnecessary verbosity.

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 (7 parameters, specialized domain) and the presence of an output schema, the description is quite complete. It explains what the tool does, what it returns, and all parameter semantics. The main gap is lack of behavioral context about computational characteristics, but with an output schema handling return values, this is less critical.

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 explaining all 7 parameters in detail. It defines what each parameter represents (e.g., 'Oil API gravity (degrees)', 'Gas specific gravity (air = 1.0)'), provides default values, and explains the correlation parameter options. This adds substantial meaning 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 comprehensive black-oil PVT properties at given conditions.' It specifies the exact properties returned (bubble point, solution GOR, etc.) and distinguishes itself from sibling tools like 'calculate_bubble_point' by offering a comprehensive calculation rather than just one property.

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 clear context by listing supported correlation sets with their defaults, which helps guide usage. However, it doesn't explicitly state when to use this tool versus alternatives like 'calculate_bubble_point' or 'calculate_gas_z' from the sibling list, nor does it mention 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.