forecast_advanced_decline

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

No annotations are provided, so description carries full burden. It discloses it generates forecasts and cumulative production but lacks details on side effects, resource usage, error conditions, or data persistence, leaving 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?

Well-structured with a clear one-liner, bullet points, and parameter details; about 150 words. Slightly verbose but efficiently conveys necessary information without excessive fluff.

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?

Covers purpose, usage, and parameter details in depth. Given the complexity of four models and multiple parameters, it is reasonably complete. Does not address error handling or edge cases, but output schema exists so return values are not needed.

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 has 0% description coverage, but the description compensates fully by listing required parameters for each model (e.g., qi, Di, Dinf, n) and explaining defaults for forecast_months and economic_limit, adding crucial meaning 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 it is for forecasting production using advanced decline models (PLE, Duong, SEPD, THM) and contrasts with sibling fit tools, distinguishing its role as the forecasting step after fitting.

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?

Explicitly says to use parameters from specific fit tools or THM parameters, providing clear when-to-use guidance. Lacks explicit when-not-to-use or alternatives, but context is adequate.

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