check_gpu_health

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 describes the tool's function and output format (Markdown report), but lacks details on permissions needed, rate limits, or whether it performs read-only operations, which are important for a cluster health check 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 well-structured with a purpose statement, a 'Why' section for context, and a 'Returns' section for output, all in three concise bullet points. Every sentence adds value without redundancy, making it efficient and front-loaded.

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 (health diagnostics across a cluster) and the presence of an output schema, the description is mostly complete, covering purpose, usage context, and output format. However, it could benefit from more behavioral details like authentication or error handling, which are not fully compensated by the output schema alone.

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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the inputs. The description does not need to add parameter details, and it appropriately focuses on the tool's purpose and output, earning a baseline score above 3 due to no parameters.

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 with specific verbs ('check for GPU hardware errors and throttling events') and resources ('across the cluster'), distinguishing it from siblings like get_gpu_utilization or inspect_gpu_pod by focusing on health diagnostics rather than metrics or detailed pod inspection.

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 'Why' section provides clear context for when to use this tool (detect hardware failures, explain performance issues), but it does not explicitly state when not to use it or name alternatives among siblings, such as get_gpu_utilization for utilization metrics instead of health issues.

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