calculate_net_pay

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

Since no annotations are provided, the description carries full burden. It discloses that the tool calculates net pay properties and pay flags, indicating a non-destructive read operation. However, it does not mention error handling, input validation requirements, or side effects. The description adds context beyond the schema but lacks full behavioral disclosure.

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 concise and well-structured: a one-line summary, a bullet list of returns, and a formatted Args section. Every sentence is necessary and adds value. No redundant information.

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?

The description covers the tool's functionality, inputs, and outputs, even noting the presence of an output schema. However, it omits critical constraints like that input arrays must have equal length or that values should be within reasonable ranges (e.g., porosity between 0 and 1). These gaps could lead to errors if not checked elsewhere.

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?

The description provides detailed explanations for each parameter in the Args section, including units (e.g., 'Measured depths (ft)') and default values for cutoff parameters. This fully compensates for the 0% schema description coverage, as the schema only includes titles and types. The description adds significant meaning beyond the structured fields.

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's purpose: 'Determine net pay by applying porosity, Sw, and Vshale cutoffs to log data.' It specifies the verb ('determine'), resource ('net pay'), and method ('applying cutoffs'). The returned values are listed, making the tool's scope unambiguous. While sibling tools include other 'calculate_' functions, none directly duplicate net pay calculation, so differentiation is not necessary.

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 its input parameters (log data and cutoffs), but it does not explicitly state when to use this tool over alternatives. No guidance is provided on prerequisites (e.g., array lengths must match) or situations to avoid. The usage is inferred but not directly instructed.

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