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 of behavioral disclosure. While it states the calculation method (Hammerschmidt equation) and supported inhibitors, it doesn't describe output format, units of the injection rate result, error conditions, or computational limitations. For a calculation tool with no annotation coverage, this leaves significant behavioral 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 a clear purpose statement, supported inhibitors list, and parameter explanations in a labeled 'Args:' section. Every sentence serves a purpose, though the parameter explanations could be slightly more concise by avoiding repetition of units in parameter names.

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 has an output schema (which handles return values), no annotations, and good parameter coverage in the description, the description is reasonably complete. However, it could better address behavioral aspects like calculation assumptions, limitations, or typical use cases to reach full completeness for this engineering calculation tool.

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 4 parameters: units ('degrees F', 'bbl/day'), purpose ('hydrate formation temperature', 'target operating temperature'), and valid values for the inhibitor parameter ('methanol', 'meg', or 'ethanol'). This adds substantial value beyond the bare schema.

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 hydrate inhibitor injection rate') and method ('using Hammerschmidt equation'), with explicit resource scope. It distinguishes from sibling tools like 'calculate_hydrate_temp' by focusing on injection rate calculation rather than temperature determination.

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 parameter explanations (e.g., 'hydrate formation temperature', 'target operating temperature'), but doesn't explicitly state when to use this tool versus alternatives like 'calculate_hydrate_temp' or other engineering calculations. No explicit when-not-to-use guidance or prerequisite information is provided.

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