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SkillsMP は tosin2013/rhel-devops-skills-cli から 16 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
収集済み skill 16 件中 16 件を表示しています。
AI assistance for building RHDP Catalog Items using the Field-Sourced Content Template — a self-service GitOps platform with Helm and Ansible deployment patterns. Use when creating demos or labs for Red Hat Demo Platform.
原文の言語: 英語
Project onboarding assistant that reads onboard.yml manifests to install prerequisites, configure environments, and validate deployment readiness for AgnosticD workshops, demos, and validated patterns. Use when a user clones a project and asks for help…
原文の言語: 英語
AI assistance for Showroom — the RHDP lab guide and terminal system. Use when creating Antora-based lab content, configuring Showroom deployment on OpenShift (terminal types, VNC, multi-user), or integrating Showroom with AgnosticD or Field-Sourced Content.
原文の言語: 英語
AI assistance for verifying that a deployed workshop or demo environment is ready for students. Use when a developer provides OpenShift credentials or bastion access and asks whether students can start the lab. Adapts to OCP, RHEL VM, AAP, and hybrid…
原文の言語: 英語
AI assistance for architecting, sizing, provisioning, and validating an AgnosticD deployment where Showroom runs on a dedicated hub cluster and students each get their own SNO or compact OpenShift cluster. Covers student count input (default 2), cloud…
原文の言語: 英語
Audit projects against RHEL DevOps standards — AgnosticD configs, onboard.yml manifests, deployed environments, and project structure. Produces structured PASS/WARN/FAIL reports with prioritized remediation plans containing executable commands. A meta-auditor…
原文の言語: 英語
AI assistance for validating an AgnosticD v2 deployment end-to-end — verifying provisioning completed cleanly, all workloads are running, agnosticd_user_info data is flowing, and the stop/start/status lifecycle works. Use after agd provision completes, before…
原文の言語: 英語
AI assistance for AgnosticD v2 — the Ansible Agnostic Deployer for provisioning infrastructure and deploying workloads on AWS, Azure, OpenStack, and OpenShift. Use when working with the agd CLI, catalog items, configs, or deployment workflows.
原文の言語: 英語
AI assistance for Patternizer — a CLI tool that bootstraps Git repositories containing Helm charts into ready-to-use Validated Patterns for OpenShift. Use when initializing, upgrading, or working with Validated Patterns.
原文の言語: 英語
AI assistance for resolving open research questions in the skill catalog. Use when a user wants to answer a (RESEARCH NEEDED — RQ-N) question, fetch upstream documentation and write findings permanently into the affected skill files, or propagate research…
原文の言語: 英語
AI assistance for validating a Validated Pattern deployment end-to-end — verifying VP Operator installation, ArgoCD Application convergence, secrets delivery via Vault and ESO, and imperative job completion. Use after pattern.sh make install or VP Operator…
原文の言語: 英語
AI assistance for validating the health of an already-running Validated Pattern deployment — checking ArgoCD Application convergence, secrets delivery, and job completion without re-installing. Use when the pattern was deployed by automation or by someone…
原文の言語: 英語
AI assistance for auditing and improving existing Validated Pattern repos against VP Operator requirements and Sandbox/Tested/Maintained tier criteria. Use when a developer has run `patternizer init` and needs to know what to fill in, or when preparing a…
原文の言語: 英語
AI assistance for auditing a Validated Pattern against VP tier requirements (Community/Sandbox, Tested, Maintained) and guiding submission to validatedpatterns/docs. Use after vp-deploy-validator reports HEALTHY and the pattern deploys fully without user…
原文の言語: 英語
AI assistance for auditing and improving existing AgnosticD v2 configs and workload roles against RHDP best practices. Use when a developer has an existing deployment and wants to improve it, fix validation failures, or prepare it for RHDP submission — not…
原文の言語: 英語
AI-as-student module testing — reads a workshop module (AsciiDoc or markdown), executes each student step against a live environment, verifies expected outcomes, classifies failures, and produces a step-by-step pass/fail report. Use when a developer asks to…
原文の言語: 英語