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 but only states what it calculates without behavioral details. It doesn't disclose computational characteristics (e.g., numerical stability, array length requirements), error conditions, or output format expectations beyond the listed variables. For a 5-parameter calculation tool with no annotation coverage, this is insufficient.

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: a clear purpose statement followed by a bullet-like Args section with exactly one line per parameter. Every sentence earns its place, with zero redundant information or unnecessary elaboration.

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 (5 required parameters, specialized reservoir engineering calculation) and the presence of an output schema (which handles return values), the description is reasonably complete. It explains what the tool does and what each parameter represents, though it could benefit from more behavioral context given the lack of annotations.

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?

Schema description coverage is 0%, but the description provides clear semantic explanations for all 5 parameters in the Args section, mapping each parameter to its physical meaning (e.g., 'Bottomhole flowing pressures (psi)'). This compensates well for the schema's lack of descriptions, though it doesn't specify units for 'times' beyond 'days or months' or validation rules.

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 ('Compute Agarwal-Gardner rate-normalized variables') and the domain context ('for type curve analysis'), distinguishing it from sibling tools like 'rta_blasingame' or 'rta_normalized_rate' which perform different reservoir analysis calculations.

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 'for type curve analysis' and the parameter list suggests it's for reservoir engineering workflows, but it doesn't explicitly state when to use this tool versus alternatives like 'rta_blasingame' or 'rta_material_balance_time' which are also RTA (Rate Transient Analysis) methods.

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