get_latest

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

Beyond the annotations, the description discloses key behavioral traits: it consumes one unit of the monthly AuraStream allowance, returns historical/delayed data rather than live quotes, and notes that the last bar may still be forming. These are exactly the caveats an agent needs before calling the tool.

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 three short sentences, front-loaded with the purpose and followed by quota and data-quality caveats. Every sentence adds useful information with no wasted text.

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, full parameter documentation, and annotations already covering safety and idempotency, the description supplies the remaining quota and delayed-data caveats. It could explicitly name get_timeseries as the alternative, but it is otherwise complete enough for correct invocation.

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 description coverage is 100%, so the schema already documents all four parameters including enums and defaults. The description reinforces that bars are returned per ticker but adds no syntax or constraints beyond what the schema provides, so the baseline of 3 is appropriate.

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 states a specific verb and resource: return the most recent N OHLCV bars per ticker. The phrase 'without having to pick dates' implicitly contrasts with get_timeseries, but it does not explicitly name the sibling, so the differentiation is clear but not fully explicit.

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 phrase 'without having to pick dates' signals the convenience scenario, but the description never names get_timeseries or states when not to use this tool. The alternative is left to inference rather than explicitly routed.

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