havlena_odeh

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

With no annotations, the description must carry the transparency burden. It explains the method and inputs but omits behavioral details such as assumptions, numerical stability, error handling, or data quality requirements. The method and return type are stated, but deeper behavioral traits are missing.

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 front-loaded with purpose and method, followed by a systematic parameter list. While lengthy, every sentence adds value. It could be slightly trimmed without loss but is well-organized.

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 complexity (14 params, output schema exists), the description covers the core functionality, input semantics, and high-level output. It does not detail the output structure but relies on the output schema. Some additional context on drive mechanism indicators would improve completeness.

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 compensates for the schema's 0% coverage by detailing each parameter with units and context (e.g., 'pressures (psi)', 'np_values (STB)'). This adds significant meaning beyond the schema's names and types.

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 explicitly names the Havlena-Odeh straight-line method, identifies its purpose (oil material balance, drive mechanism identification, OOIP estimation), and defines the output (F vs Et plot data). This clearly distinguishes it from sibling reservoir tools.

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 when pressure and production data are available but does not specify when to use this tool over alternatives like pz_analysis or volumetric_ooip. No explicit when-not or exclusion criteria are provided.

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