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check_pod_health

Check Kubernetes pod health status, with options to filter only failed pods, specify namespace, pod name, and cluster.

Instructions

检查Pod健康状态,支持筛选失败的Pod

Args: pod_name: Pod名称,如果不提供则检查命名空间中的所有Pod namespace: Kubernetes命名空间 kubeconfig_path: kubeconfig 文件路径,不指定则使用 cluster_name 或默认集群 cluster_name: 集群配置名称(clusters.json 中的 name),kubeconfig_path 未指定时使用 only_failed: 是否只返回失败或异常的Pod,默认为False limit: 当检查命名空间内所有 Pod 时,最多处理的 Pod 数量,默认 100,避免大量 Pod 时过慢

Returns: Pod健康状态报告,包含失败Pod筛选功能

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
pod_nameNo
namespaceNodefault
only_failedNo
cluster_nameNo
kubeconfig_pathNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses defaults (namespace, only_failed, limit) and that limit avoids slowness with many Pods, but it does not explicitly state read-only behavior, what health criteria are used, or any permission requirements. A health check implies non-destructive action, but the implications are not made explicit.

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 front-loaded with the core purpose, then uses a clean Args list for parameters and a Returns line. Each bullet adds necessary information without fluff, making it easy to scan and parse.

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 no output schema and no annotations, the description covers all parameters and core behavior but the Returns statement is vague ('Pod健康状态报告' - Pod health status report). It does not specify what fields or status values will be included, so an agent cannot predict the report structure precisely. Still, the essential execution context is covered.

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

Parameters5/5

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

The schema has 0% description coverage, but the Args block explains all 6 parameters with meaningful semantics: pod_name optional, namespace default, kubeconfig_path fallback to cluster_name, only_failed default False, and limit default 100 with rationale. This fully compensates for the schema's lack of descriptions.

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

Purpose5/5

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

The description begins with a specific verb and resource: '检查Pod健康状态' (check Pod health status), clearly distinguishing it from sibling tools like check_cluster_health and check_node_health. It also mentions a distinct capability, '支持筛选失败的Pod' (supports filtering failed Pods).

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

Usage Guidelines4/5

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

The description clearly establishes when to use the tool by naming the resource (Pod health) and using namespace/cluster parameters. It does not explicitly mention alternative tools or when-not-to-use scenarios, but the context is clear enough for an agent to select it over cluster/node health checks.

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

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