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 for behavioral disclosure. While it states what the tool calculates, it doesn't describe important behavioral aspects: whether this is a read-only computation or modifies data, what format the output takes, whether there are validation requirements for input arrays, or any computational constraints. The description is purely functional without 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 perfectly structured and concise. It opens with the core purpose, explains what the tool calculates, then provides a clean parameter section with clear explanations. Every sentence earns its place, with no redundant or vague language. The parameter explanations are bullet-like but formatted as a cohesive paragraph.

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 complexity of a 5-parameter reservoir engineering calculation with no annotations, the description adequately covers the purpose and parameter semantics. However, it lacks behavioral context and usage guidelines. The presence of an output schema (not shown here) means the description doesn't need to explain return values, but it should still address when and how to use this specific RTA method versus alternatives available in the extensive sibling tool list.

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 adds substantial value by explaining each parameter's meaning and units. It clarifies that 'times' are in 'days or months,' 'rates' are 'production rates,' 'cumulative' is 'cumulative production,' 'flowing_pressures' are 'Bottomhole flowing pressures (psi),' and 'initial_pressure' is 'Initial reservoir pressure (psi).' This transforms cryptic parameter names into meaningful domain-specific inputs.

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 purpose: 'Compute Blasingame rate-normalized integral and derivative for type curve matching.' It names the exact mathematical technique (Blasingame decline type curve analysis) and lists the specific outputs (material balance time, normalized rate, rate-integral, rate-integral-derivative). This distinguishes it from sibling tools like 'rta_agarwal_gardner' or 'rta_material_balance_time' which perform different rate transient 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 provides no guidance on when to use this tool versus alternatives. While it mentions 'type curve matching' and 'Blasingame decline type curve analysis,' it doesn't specify when this analysis is appropriate compared to other RTA methods available in the sibling tools. There are no prerequisites, exclusions, or comparative recommendations provided.

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