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 describes what the tool does (plots regression, estimates volumes) but doesn't disclose behavioral traits like whether it returns a plot, numerical results, or both; error handling; computational requirements; or limitations of the method. The description is technically accurate but lacks operational context.

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 purpose statement, methodology explanation, and parameter documentation. It's appropriately sized for a technical tool with 5 parameters. Minor improvement could be front-loading the parameter section more clearly, but overall it's efficient with minimal waste.

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 technical complexity, 5 parameters with 0% schema coverage, and presence of an output schema, the description does well. It explains the methodology and parameters thoroughly. The output schema existence means the description doesn't need to explain return values. It could benefit from mentioning typical use cases or limitations, but it's largely complete for the tool's purpose.

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 providing clear semantic explanations for all 5 parameters: what each represents, expected units, and their role in the calculation. The Args section adds substantial value beyond the bare parameter names in the schema, making the tool much more usable.

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: 'estimate OOIP/OGIP from production data' with specific methodology ('Plots q/(Pi-Pwf) vs normalized cumulative production') and outcome ('x-intercept gives the contacted hydrocarbon volume'). It distinguishes from siblings like 'volumetric_ooip' by specifying it's a flowing material balance method using production data rather than volumetric calculation.

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 when to use this tool (for estimating original oil/gas in place from production data) and distinguishes it from volumetric methods. However, it doesn't explicitly mention when NOT to use it or provide specific alternatives among the many sibling tools, though the methodology description helps differentiate it from other RTA tools like 'rta_blasingame' or 'rta_agarwal_gardner'.

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