Add use-inlets-operator skill

[welteki]

Description

Add the use-inlets-operator skill to guide agents through installing and operating inlets-operator for Kubernetes LoadBalancer Services.

The skill covers:

• Cloud-provider, region, credential, and license setup.
• Existing LoadBalancer controller detection and annotated-only operation.
• Service and Tunnel CR inspection.
• Tunnel recreation and cloud infrastructure lifecycle.
• Safe credential handling, verification, troubleshooting, and cleanup.

Also adds skill interface metadata and lists the skill in the README.

Motivation and context

Provide agents with current guidance for exposing Kubernetes Services through inlets-operator and safely managing the associated cloud infrastructure lifecycle.

How has this been tested?

• Validated the skill structure with the skill validation tool.
• Checked the committed diff for whitespace and formatting errors.
• Tested against a Slicer K3s cluster and Hetzner using OpenCode with Qwen3.6-27B-FP8-vLLM.
• Exercised operator installation, annotated LoadBalancer provisioning, public HTTP access, Tunnel recreation, and complete Kubernetes and cloud-resource cleanup.

[reviewfn]

AI Pull Request Overview

Disclaimer: This review was generated by automated AI and may contain errors. Do not trust its outputs without human verification.

Summary

• Adds a new use-inlets-operator skill for installing, inspecting, operating, recreating, and cleaning up inlets-operator-managed Kubernetes LoadBalancer tunnels.
• Adds OpenAI interface metadata for the new skill.
• Lists the new skill in the repository README.
• The skill is safety-oriented around cloud credentials, Kubernetes Secrets, existing LoadBalancer controllers, and destructive cleanup.
• No blocking correctness, rendering, or publish-quality findings were identified in the scoped diff.

Approval rating (1-10)

9/10. The PR is coherent and ready to merge; only minor wording precision could improve reader clarity.

Summary per file

Summary per file

File path	Summary
README.md	Adds the new inlets-operator skill to the skills table.
skills/use-inlets-operator/SKILL.md	Defines workflow guidance for inlets-operator installation, exposure, lifecycle, and cleanup.
skills/use-inlets-operator/agents/openai.yaml	Adds OpenAI interface metadata and a default prompt.

Overall Assessment

The new skill fits the repository structure and gives agents practical, safety-conscious guidance for using inlets-operator with Kubernetes LoadBalancer Services. The content covers the main operational risks: existing LoadBalancer controllers, secret handling, tunnel recreation versus final cleanup, and verification before destructive actions. I did not find a concrete issue that should block merging.

Detailed Review

Detailed Review

Content review

No blocking findings.

• The title and front matter description match the body: this is clearly about operating inlets-operator through Kubernetes resources rather than managing standalone tunnels.
• The opening establishes the mental model for Services, Tunnel CRs, cloud VMs, and public IP assignment before presenting commands, which helps avoid misuse.
• The structure is usable for agents: install, expose, lifecycle, cleanup, and troubleshooting are separated in the order a user is likely to need them.
• The examples are appropriately cautious about credentials and destructive operations. The placeholder resource names are clear enough, though future revisions could add a short reminder to discover the generated Tunnel name from the cluster before copying cleanup commands verbatim.

AI agent details.

Agent processing time: 1m24.342s
Environment preparation time: 2.965s
Total time from webhook: 1m29.469s