GPU Infrastructure Scan

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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating safety. The description adds behavioral detail (e.g., probing DCGM endpoints on port 9400 for unauthenticated metrics leak detection), providing context beyond annotations. No contradictions.

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?

Single sentence that succinctly captures the tool's purpose and scope with no wasted words. Front-loaded with the key verb and resource types.

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 presence of annotations (readOnly, idempotent, openWorld), an output schema (not shown but noted), and 100% parameter coverage in schema, the description adequately completes the picture. It identifies what the tool discovers without needing to explain return values.

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 both parameters already well-described in the input schema (k8s_context for K8s context, probe_dcgm for DCGM probing). The description adds little beyond framing the overall purpose.

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 the verb 'Discover' with specific resource types: containers, K8s nodes, and DCGM endpoints. It clearly differentiates from siblings like ai_inventory_scan or scan by focusing on GPU/AI compute infrastructure.

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 use for GPU infrastructure discovery but provides no explicit when-to-use or when-not-to-use guidance, nor does it compare to sibling tools.

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