petropt/petro-mcp

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

No annotations are provided, so the description carries full burden. It states the tool performs a calculation but doesn't disclose behavioral traits like error handling, performance characteristics, or whether it's a pure function. The description adds minimal context beyond the basic operation, leaving gaps in understanding how it behaves under different conditions.

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 efficiently structured with a clear purpose statement followed by a bullet-point-like parameter explanation. Every sentence adds value: the first defines the tool's function, and the subsequent lines document parameters without redundancy. It's front-loaded and wastes no words.

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 moderate complexity (4 parameters, no annotations, but with an output schema), the description is largely complete. It covers all parameters semantically and states the purpose clearly. The output schema likely handles return values, so the description doesn't need to explain them. However, it could improve by adding more behavioral context or usage guidance.

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, the description fully compensates by explaining all four parameters: 'gr' (Gamma ray reading), 'gr_clean' (GR in clean sand), 'gr_shale' (GR in pure shale), and 'method' (Calculation method with default 'linear'). It provides essential semantic meaning that the schema lacks, including units (API units) and method options.

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 ('Calculate shale volume') and resource ('from gamma ray log'), distinguishing it from siblings like 'calculate_annular_velocity' or 'calculate_archie_sw' which perform different petroleum engineering calculations. It explicitly names the four calculation methods, making the purpose unambiguous.

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 context through the parameter explanations (e.g., 'gr_clean: GR in clean sand'), suggesting this tool is for gamma ray log analysis. However, it doesn't explicitly state when to use this tool versus alternatives like 'calculate_effective_porosity' or other petrophysical calculations, nor does it mention prerequisites or exclusions.

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