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

The annotations already provide strong behavioral hints (readOnlyHint: true, destructiveHint: false). The description itself offers no additional behavioral context beyond the inherent nature of historical, read-only data.

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 brief and effective. It front-loads the function and provides a helpful, targeted example of its use case in a single concise paragraph.

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?

While the annotations are comprehensive, the description lacks completeness regarding the temporal boundaries of the data (e.g., how far back the observations go) and parameter intent, which is a noticeable gap given the low schema coverage signal.

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?

With only 50% schema description coverage, the description fails to add meaningful semantic value. It relies entirely on the schema to define the parameters and doesn't clarify the importance of specific parameters like marketType in filtering the timeline.

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 is highly specific, defining the resource as a timeline of odds movement and the data as timestamped observations. It functions as a clear verbal specification of the API's function.

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?

It provides a clear use case ('how has the line moved'), but it does not offer guidance on when this tool should be used relative to the broader suite of aura tools (e.g., when to use this over a simple market snapshot).

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