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jasamandehvary

kahlo-mcp

exec_in_pod

Run shell commands inside a Kubernetes pod or container to retrieve output, enabling direct inspection and troubleshooting of deployment health.

Instructions

Run a shell command inside a pod (or one of its containers, including an ephemeral debug container previously created with spawn_ephemeral_debug_container) and return its combined output. This is how you actually use a spawned debug container once it's running.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
podYes
commandYes
containerNo
namespaceNodefault
timeout_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the core behavior and that output is combined, and it correctly situates the tool relative to spawned debug containers. However, it does not mention potential side effects of running arbitrary commands, timeout/exit-code behavior, or prerequisites like the pod/container needing to be running.

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 two sentences with no wasted words. The core operation is front-loaded, and the second sentence adds valuable context about the companion spawn tool rather than repeating obvious details.

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-value details are not the description's responsibility. Still, the tool has a moderate parameter count, no annotations, and relevant siblings such as get_pod_logs and spawn_ephemeral_debug_container; the description provides the key intended use but leaves out prerequisites, timeout semantics, and explicit alternative routing.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It partially explains pod, command, and container selection through natural language, but it does not clarify timeout_seconds, namespace defaults, or what happens when container is left empty. With five parameters and no schema descriptions, this is a meaningful gap.

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 clearly states the verb and resource: run a shell command inside a pod and return its combined output. It also distinguishes itself from the sibling spawn_ephemeral_debug_container by explaining that this tool is how you use a debug container once it is running.

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 gives clear usage context: it is meant for executing commands in a running container, particularly ephemeral debug containers created by spawn_ephemeral_debug_container. It does not explicitly state when not to use it or compare against alternatives like get_pod_logs, so it stops short of full when/when-not guidance.

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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