get_bytes_processed_metrics

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

Annotations provide readOnlyHint=true, indicating this is a safe read operation. The description adds value by specifying the return structure (e.g., success flag, breakdowns, totals) and permissions ('Read Panther Metrics'), which aren't covered by annotations. However, it doesn't disclose other behavioral traits like rate limits, caching, or error handling. With annotations handling the safety profile, the description offers moderate additional context, aligning with a baseline score.

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 appropriately sized and front-loaded, starting with the core purpose. The 'Returns' section is detailed but necessary for clarity, and the permissions note is concise. However, the structure could be slightly improved by integrating the permissions into the main flow or using bullet points for better readability, but overall, it's efficient with minimal waste.

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 tool's complexity (3 parameters, 100% schema coverage, annotations, and an output schema implied by the return description), the description is fairly complete. It explains what the tool does, the return format, and permissions. The output schema details in the description compensate for the lack of a formal output schema field. However, it could benefit from more usage context or examples to fully guide the agent, keeping it from a perfect score.

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%, with each parameter (start_date, end_date, interval_in_minutes) well-documented in the schema. The description doesn't add any parameter-specific details beyond what's in the schema, such as explaining how the interval affects the 'bytes_processed' list. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description provides no extra parameter semantics.

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's purpose: 'Retrieves data ingestion metrics showing total bytes processed per log type and source, helping analyze data volume patterns.' It specifies the verb ('Retrieves'), resource ('data ingestion metrics'), and scope ('per log type and source'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_rule_alert_metrics' or 'get_severity_alert_metrics', which also retrieve metrics but for different aspects, so it doesn't reach the highest score.

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. It mentions analyzing 'data volume patterns,' but doesn't specify scenarios, prerequisites, or exclusions. For example, it doesn't clarify if this is for real-time monitoring, historical analysis, or how it compares to other metrics tools in the sibling list. This lack of context leaves the agent without clear usage direction.

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