petropt/petro-mcp

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

No annotations are provided, so the description carries the full burden. It discloses the mathematical model (Gilbert correlation) and its validity condition (critical flow only), which are important behavioral traits. However, it lacks details on error handling, units of the output (implied but not stated), or performance characteristics like computational limits.

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 front-loaded with the core purpose and formula, followed by a structured 'Args:' section. Every sentence earns its place: the first two sentences define the tool and its constraints, and the parameter explanations are necessary given the lack of schema descriptions. No redundant information is present.

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 (engineering calculation with 6 parameters), no annotations, and an output schema (implied by 'Has output schema: true'), the description is largely complete. It covers the formula, validity, and all parameters thoroughly. However, it does not explicitly state the output's nature (e.g., flow rate in specific units), relying on the output schema, which is acceptable but leaves a minor gap for full context.

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%, so the description must compensate fully. It provides detailed semantics for all 6 parameters: explaining what each represents (e.g., 'upstream pressure in psi'), units (e.g., 'scf/bbl'), ranges (e.g., '0-1' for water cut), and defaults. This adds significant meaning beyond the bare schema titles.

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 flow rate through a choke') and the method ('using Gilbert correlation (1954)'), distinguishing it from sibling tools like 'calculate_annular_velocity' or 'calculate_ecd' which address different engineering calculations. It provides a precise mathematical formula, 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 explicitly states 'Valid for critical (sonic) flow only,' which provides clear context for when to use this tool. However, it does not mention when not to use it (e.g., for subcritical flow) or name specific alternatives among the many sibling tools, such as 'calculate_turner_critical' which might handle different flow regimes.

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