detect_pod_restarts_anomalies

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context about what the tool detects (unstable pods, high restart rates) and why (application stability, proactive detection), but does not specify permissions needed, rate limits, or detailed output behavior beyond a 'Markdown report'. This leaves gaps in understanding operational constraints.

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 well-structured and front-loaded with the core purpose, followed by a 'Why' section for context, and clear sections for 'Args' and 'Returns'. Every sentence adds value without redundancy, making it efficient and easy to parse for an agent.

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 moderate complexity (2 parameters, no annotations, but an output schema exists), the description is largely complete. It covers purpose, parameters, and return format, and the output schema handles return values. However, it lacks details on permissions, error handling, or integration with sibling tools, which could enhance completeness.

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 description coverage is 0%, so the description must compensate. It adds meaningful semantics for both parameters: 'threshold' is explained as 'Minimum number of restarts to flag' with a default, and 'duration' as 'Window of time to analyze' with examples. This clarifies usage beyond the bare schema, though it could provide more detail on duration formats or threshold rationale.

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 specific action ('identify unstable pods experiencing high restart rates') and distinguishes this tool from siblings like get_pod_diagnostics or get_pod_logs by focusing on restart rate anomalies rather than general diagnostics or logs. The 'Why' section reinforces this purpose by explaining it's an application stability indicator for proactive detection.

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 implies usage for monitoring pod stability and catching intermittent failures, but does not explicitly state when to use this tool versus alternatives like get_pod_diagnostics or inspect_gpu_pod. No exclusions or specific prerequisites are mentioned, leaving the agent to infer context from the purpose alone.

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