energy_oil_detail

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds the source URL and return type (DataFrame) but no deeper behavioral traits such as rate limits, pagination, or data granularity. This is adequate given the annotations, but not rich.

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 compact and well-structured, with a URL, parameter doc, return doc, and type. The first line is a noun phrase that repeats the title, but the additional elements (URL, parameter guidance) earn their place. It is not verbose and front-loads the core 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?

For a tool with one optional parameter and no output schema, the description gives the return type and a hint for parameter discovery. It lacks details on DataFrame columns or regional scope, which could reduce usability, but given the low complexity and strong annotations, it is minimally complete.

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 schema has one parameter 'date' with no description (0% coverage). The description explains the date is an oil price adjustment time and points to energy_oil_hist() for valid values, adding meaning beyond the schema. However, it does not explicitly state the format (only the default implies YYYYMMDD), so it partially compensates for the lack of schema coverage.

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 provides gasoline and diesel oil prices across regions, and the :return section confirms it returns oil price for a specific date. This distinguishes its purpose (detail data for a given date) from siblings like energy_oil_hist (historical adjustment dates), though it does not explicitly name the alternative.

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 parameter documentation explicitly instructs to call ak.energy_oil_hist() to obtain valid adjustment dates, which tells the agent how to source the required date and implicitly when to use this tool (for a specific date). It lacks explicit 'when not to use' statements but provides clear contextual guidance.

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