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kubectl_logs

Fetch log lines from a Kubernetes pod container by cluster, namespace, and pod to debug application issues without SSH access.

Instructions

Fetch log lines from a pod's container in a Kubernetes cluster.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
podYespod name to fetch logs for
tailNonumber of most recent log lines to return (default: all available)
clusterYesthe inventory kubernetes cluster name
containerNocontainer name (default: the pod's only/first container)
namespaceYesnamespace the pod is in

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
podYes
logsYes
clusterYes
containerNo
namespaceYes
timestampYes
line_countYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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. It only says 'Fetch,' implying a read-only operation, but omits auth requirements, rate limits, behavior for multi-container pods, or whether the call is streaming versus snapshot.

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 front-loaded sentence with zero waste. It states the action and resource immediately and contains no redundant or filler content.

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

Completeness3/5

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

An output schema exists, so return values need not be described, and schema coverage is full. However, with no annotations and no usage guidance, the description does not fully compensate for the missing behavioral and routing context an agent needs among multiple log-fetching siblings.

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 all five parameters including defaults for 'tail' and 'container'. The description adds no parameter semantics beyond what the schema provides, making the baseline 3 appropriate.

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 states a specific verb ('Fetch') and resource ('log lines from a pod's container in a Kubernetes cluster'). The resource scope naturally distinguishes it from sibling tools like docker_logs, cisco_logs, kubectl_describe, and kubectl_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?

No when-to-use guidance, prerequisites, or alternative tools are mentioned. The description implies usage context but provides no explicit routing information for an agent choosing among the many log-related siblings.

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