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raviraj-ntp

Dynatrace MCP

by raviraj-ntp

Kubernetes Events

dynatrace_k8s_events

Query Kubernetes cluster, pod, and workload events in a specified time range to diagnose outages, crashes, and scheduling problems.

Instructions

Kubernetes cluster/pod/workload events in a time range.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd: now or ISO-8601
podNoPod name: exact replica, prefix ending with '-', or glob (my-app-*).
fromNoStart: now-30m or ISO-8601
limitNo
aroundNoPivot timestamp for a window
windowNoHalf-window around pivot, e.g. 2m
clusterNoDynatrace k8s.cluster.name. Discover with dynatrace_list_clusters; do not assume a cluster.
endDateNoCalendar end YYYY-MM-DD (UTC day)
findAllNo
workloadNoWorkload or deployment name (k8s.workload.name / k8s.deployment.name).
namespaceNoKubernetes namespace (k8s.namespace.name). Discover with dynatrace_list_namespaces.
startDateNoCalendar start YYYY-MM-DD (UTC day)
connectionNoNamed connection from env (default, optional stage/prod aliases, or a DYNATRACE_CONNECTIONS key)
allowLongRangeNoAllow ranges longer than the default cap

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.1/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses nothing: not whether this is a read-only query, what the default time-range cap is (despite an allowLongRange flag), how results are ordered or paginated, or what limits apply. For a 14-parameter tool with zero annotation coverage this is a complete gap.

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

Conciseness2/5

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

It is a single short fragment, but the brevity is under-specification rather than conciseness. For a tool with 14 parameters and no annotations, one noun phrase leaves the agent with almost nothing to front-load its decision.

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

Completeness1/5

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

Given 14 parameters, no annotations, no output schema, and a dense field of overlapping event-related siblings, the description is far too thin to let an agent call this correctly or pick it over alternatives.

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 86%, so the schema already documents nearly all 14 parameters, including the cluster/namespace discovery hints and pod pattern syntax. The description adds nothing beyond 'in a time range', which the from/to/startDate/endDate parameters already convey, so baseline 3 applies.

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

Purpose3/5

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

The fragment names the resource (Kubernetes events) and a scope (cluster/pod/workload) in a time range, which is more than a pure restatement of the name. However, it is a verbless noun phrase that never says what the tool actually does with those events, and it does not distinguish itself from close siblings like dynatrace_pod_events or dynatrace_k8s_issue_events.

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 when-to-use guidance, no exclusions, and no reference to the many overlapping siblings (pod_events, k8s_issue_events, execute_dql) that could also return event data. Usage is only weakly implied by the cluster/pod/workload scope.

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