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

With no annotations, the description carries the full behavioral burden. It discloses the 15-minute granularity and the computed statistics, which is useful context, but it does not state that the operation is read-only, mention rate limits, or describe how the data is aggregated or returned.

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 a single, front-loaded sentence that packs the key information—what is analyzed, the granularity, the statistics, and the optional filters—without any filler or redundancy.

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 query tool with four optional parameters and no output schema, the description is adequate but leaves gaps. It does not explain the return structure or behavioral traits like read-only safety, and with no annotations the agent has to infer these details.

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 coverage is 100%, so all four parameters are fully documented in the schema itself. The description adds only a high-level note that provider and symbol are optional filters and that a date range is required, without providing format or syntax details beyond what the schema already provides.

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 uses a specific verb ('Analyze') and names the resource ('15-minute oracle collector latency statistics') with enumerated metrics, making its purpose clear. It does not explicitly differentiate itself from siblings like get_feed_uptime or get_metrics, but the focus on latency statistics is distinctive enough to infer the difference.

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 provides no guidance on when to use this tool versus alternatives such as get_feed_uptime, get_metrics, or get_anomalies. It only implies its use case by stating it analyzes latency over a date range, leaving the agent to infer selection criteria.

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