rta_normalized_rate

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

Explains the mathematical operation (division by drawdown), which is good. However, with no annotations, the description does not disclose edge cases (e.g., zero drawdown, mismatched array lengths) or any destructive nature. Behavior is partially transparent.

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?

Concise: two sentences plus an Args list. Formula is front-loaded. No superfluous information; every sentence serves a purpose.

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?

With an output schema present, the lack of output description is acceptable, but the description does not mention the resulting units or potential pitfalls (e.g., zero denominator). Leaves some gaps for a preprocessing 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?

Despite 0% schema description coverage, the description's Args section adds units (bbl/d, Mcf/d, psi) and clarifies that arrays are for rate and flowing pressure. This adds significant meaning beyond the raw schema, though it could be more explicit about array length matching.

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?

Clearly states the normalization formula 'q / (Pi - Pwf)' and explains its purpose: removing pressure drawdown effects for type curve analysis and RTA. Distinguishes itself from sibling RTA tools as a preprocessing step.

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?

Mentions that the tool makes data suitable for type curve analysis and RTA, implying when to use it, but does not explicitly contrast with other normalization methods or provide when not to use it. Guidelines are implicit rather than explicit.

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