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. It explains the purpose and impact of tortuosity but lacks behavioral details like computational complexity, error handling for mismatched array lengths, whether it modifies input data, or what the output format looks like. The description doesn't contradict annotations (none exist).

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 well-structured with a purpose statement, explanation of tortuosity, and a clear parameter section. It's appropriately sized with no redundant information. The only minor improvement would be integrating the parameter explanations more seamlessly rather than using a separate 'Args:' section.

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 0% schema description coverage, the description does a reasonable job. It explains the calculation purpose and parameter meanings, but lacks behavioral context about how the calculation works, validation requirements, or error conditions. For a computational tool with no annotation coverage, more operational guidance would be helpful.

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. It provides clear semantic meaning for all four parameters: 'md' as measured depths, 'inclination' as inclinations in degrees, 'azimuth' as azimuths in degrees, and 'unit' as depth unit with default 'feet'. This adds significant value beyond the bare schema, though it doesn't specify array length requirements or value ranges.

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 tool calculates 'wellbore tortuosity index from survey data' with a specific verb ('calculate') and resource ('wellbore tortuosity index'). It distinguishes from siblings by focusing on tortuosity measurement rather than other wellbore calculations like 'calculate_dogleg_severity' or 'calculate_vertical_section'.

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?

No explicit guidance on when to use this tool versus alternatives is provided. The description explains what tortuosity measures and its impact, but doesn't specify scenarios where this calculation is preferred over other wellbore analysis tools like 'calculate_dogleg_severity' or 'calculate_well_survey'.

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