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. While it clearly describes the calculation being performed, it doesn't mention important behavioral aspects: whether this is a pure calculation (no side effects), what the output format will be, potential validation of input ranges (e.g., porosity between 0-1), or error handling. For a calculation tool with no annotation coverage, this represents significant gaps.

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 the purpose statement, formula, and parameter definitions in a logical flow. Every sentence earns its place, though the formula presentation could be slightly more readable. The information is front-loaded with the core calculation purpose immediately stated.

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 that an output schema exists (mentioned in context signals), the description doesn't need to explain return values. However, for a calculation tool with 5 parameters and no annotations, the description should ideally mention that this is a pure calculation with no side effects. The parameter semantics are excellent, but behavioral context is lacking despite the output schema covering return format.

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: clear definitions, units where applicable, and value ranges for porosity and water saturation. The Args section adds substantial value beyond what the bare schema provides, making parameter meanings completely clear.

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 calculation being performed ('Calculate volumetric Original Oil In Place'), provides the exact formula with units, and distinguishes this oil-focused tool from its sibling 'volumetric_ogip' (which presumably calculates gas in place). This is a textbook example of purpose clarity with sibling differentiation.

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. With many sibling calculation tools (like 'calculate_eur', 'calculate_npv', 'calculate_net_pay'), there's no indication of when this specific OOIP calculation is appropriate versus other petroleum engineering calculations. The description assumes the user already knows when this formula applies.

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