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Summarize failing pods

kube_pod_failure_summary
Read-only

Lists unhealthy Kubernetes pods in a namespace with failure reasons and evidence, replacing per-pod get and describe calls with one summary request.

Instructions

List unhealthy pods in a namespace with their failure reason and evidence — one call instead of get + describe per pod.

Input Schema

NameRequiredDescriptionDefault
contextNoKube context
maxItemsNoItem cap; overrides detailLevel
namespaceNoNamespacedefault
includeRawNoInclude raw/verbose fields
detailLevelNoItem preset: summary 20, normal 100, full (default; also skips the response budget)
allNamespacesNoSearch all namespaces (overrides namespace)

Output Schema

NameRequiredDescriptionDefault
podsYes
totalNo
statusYes
evidenceYes
retainedNo
truncatedNo
likelyCausesYes
suggestedNextCommandsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv5.0.1

TDQS

A3.6/5.0
Behavior3/5

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

readOnlyHint=true already declares the safety profile, so the description only needs to add operational context. It does add that failure reason and evidence are aggregated per pod, but says nothing about response size, the item cap / detailLevel trade-off, or whether evidence is truncated by the response budget mentioned in the schema.

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?

A single sentence with zero filler, front-loading the verb, resource, and payload. The round-trip savings clause is the only elaboration and it earns its place.

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?

With an output schema present and full parameter descriptions, the description needn't explain return values, and it states the essential output shape (failure reason + evidence). The one gap is that it frames the tool as namespace-scoped without mentioning the allNamespaces escape hatch, which changes what the tool does.

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 schema already documents context, maxItems, namespace, includeRaw, detailLevel, and allNamespaces. The description only echoes namespace scoping (and says "in a namespace" without acknowledging allNamespaces overrides it), adding no meaning about the detail/cap knobs.

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?

States a specific verb and resource ("List unhealthy pods in a namespace") plus what each item carries (failure reason and evidence), which is more than a restatement of the title. It does not name the sibling tools (kube_get, kube_diagnose_pod) it replaces, so differentiation must be inferred from "get + describe."

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

Usage Guidelines3/5

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

Implies the usage context — bulk triage of failing pods instead of a get+describe per pod — which is a genuine selection hint. It never says when NOT to use it (e.g., for deep single-pod investigation use kube_diagnose_pod) and offers no explicit alternative by name.

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