Matchpoint-AI AI Skills

Browse published AI skills maintained by Matchpoint-AI. Compare skill descriptions and follow each source repository for setup instructions.

7 skills

Browse skills

GitHub

terraform-state-recovery

Matchpoint-AI

Recover from Terraform state issues after infrastructure recreation. Handles orphaned resources, state drift, and cluster recovery. Use when terraform apply fails with resource conflicts.

GitHub

cross-repo-coordination

Matchpoint-AI

Coordinate changes across project-beta repositories when updating runner configurations. Ensures workflow labels match runner scale set names. Use when changing runnerScaleSetName or deploying new runner pools.

GitHub

rackspace-spot-access

Matchpoint-AI

Provides step-by-step instructions for accessing the Rackspace Spot Kubernetes cluster to debug ARC runners using spotctl. Covers installation, authentication via GCP Secret Manager, kubeconfig retrieval, and c...

GitHub

arc-runner-troubleshooting

Matchpoint-AI

Troubleshoot ARC (Actions Runner Controller) runners on Rackspace Spot Kubernetes. Diagnose stuck jobs, scaling issues, and cluster access. Activates on "runner", "ARC", "stuck job", "queued", "GitHub Actions",...

GitHub

arc-terraform-deployment

Matchpoint-AI

Deploy ARC (Actions Runner Controller) infrastructure using Terraform on Rackspace Spot. Handles CRD registration, ArgoCD installation, and namespace management. Use when deploying or troubleshooting ARC infras...

GitHub

rackspace-spot-best-practices

Matchpoint-AI

Best practices for running GitHub Actions ARC runners on Rackspace Spot Kubernetes. Covers spot instance management, preemption handling, cost optimization, and resilience strategies. Activates on "rackspace sp...

GitHub

argocd-bootstrap

Matchpoint-AI

Deploy and manage ArgoCD using the App-of-Apps pattern. Covers bootstrap Applications, ApplicationSets, and GitOps workflows. Use when setting up or troubleshooting ArgoCD deployments.

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.