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ranson21

kube-diagnostics-mcp

by ranson21

get_hpa_status

Check Kubernetes HorizontalPodAutoscaler status to identify current and target metrics, at-max capacity, and unable-to-scale conditions, helping diagnose scaling issues.

Instructions

HorizontalPodAutoscalers: current/target metrics, at-max, unable-to-scale conditions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceNoKubernetes namespace (required: no default configured; see list_namespaces)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description bears the full burden. It does disclose the nature of the output by naming the status categories returned. However, it does not clarify whether all HPAs in the namespace are returned, how missing data is represented, or whether any read permissions are needed; this is acceptable for a simple getter but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single compact, front-loaded line with no filler. Every component listed (current/target metrics, at-max, unable-to-scale conditions) adds meaningful information an agent needs to understand the tool's output.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter, read-only status tool with no output schema, the description covers the resource and the key status categories sufficiently. It could add a bit more context about the meaning of 'at-max' or the shape of conditions, but those are reasonably inferable from Kubernetes HPA terminology.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the namespace parameter is already fully documented in the schema, including a pointer to list_namespaces. The tool description adds no additional parameter meaning beyond the resource context, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies the resource (HorizontalPodAutoscalers) and the specific status information returned: current/target metrics, at-max, and unable-to-scale conditions. This clearly differentiates it from general metrics tools like query_metrics, though it does not explicitly name or contrast sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives such as get_pod_status or get_golden_signals. The only usage hint, 'see list_namespaces', lives inside the parameter schema rather than the description and concerns argument lookup rather than tool selection.

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