GIGA Cloud Learning Skills

This repository packages nine public-safe agent skills for Claude Code, Codex, and direct skill installation. Learners can ask questions, learn concepts, build bounded artifacts, challenge claims, review architecture or syntax, and operate the Chapter 3 and 4 practical paths from protected working copies.

Skill system

giga-cloud-learning-guide is the cross-chapter learning coordinator. It keeps one case coherent, selects the earliest chapter that owns an unresolved question, enforces handoff contracts, reconciles conflicting findings, and reports architecture, content, syntax, and evidence separately. It is a skill of skills with its own task, not a directory of names.

Scope	Skill	Learner result
Chapters 1 to 4	giga-cloud-learning-guide	Route, mode, handoff continuity, challenge, and final quality envelope
Chapter 1	workload-cloud-fit-assessment	A bounded service and workload profile
Chapter 1	cloud-delivery-model-advisor	A three-axis operating-arrangement comparison
Chapters 1 to 4	cloud-interoperability-explainer	Interoperability, portability, dependency, and exit findings
Chapters 1 to 4	cloud-decision-gap-discovery	Prioritised evidence gaps and stop conditions
Chapter 1	cloud-decision-matrix-steward	A reviewable service-arrangement decision record
Chapter 2	public-service-platform-architecture	A foundation-readiness architecture brief
Chapter 3	iaas-foundation-practitioner	An IaaS baseline plus a portable OpenStack tenant-resource operator kit
Chapter 4	kubernetes-cluster-lifecycle-practitioner	A cluster-runtime baseline plus a portable CAPI/CAPO operator kit

The package intentionally uses nine coherent skills rather than separate skills for every OpenStack service, client interface, Kubernetes controller, or lifecycle operation.

Learning contract

• ask: answer directly and separate transferable concepts, product mappings, assumptions, evidence status, and named sources.
• learn: teach one bounded concept through a concrete service case, then test understanding.
• work: use Spec -> Run -> Validation. Repeat. to produce a chapter handoff without inventing local facts.
• challenge: obtain the learner's claim or attempted answer, then test assumptions, failure paths, ownership, and evidence.
• review: return independent architecture, content, syntax, and evidence verdicts with repair actions.

The machine-readable route and coverage contract is learning-contract.json. Human-readable handoffs are in docs/handoff-contracts.md. Reviewed chapter revisions and known source tensions are in docs/source-and-scope-map.md.

Practical operator paths

The Chapter 3 and Chapter 4 practitioner skills include commit-pinned operator kits under their local assets/operator-kit/ directories. In work mode they support assess, prepare, provision, validate, maintain, and cleanup with explain, prepare, or execute intent.

A practical run always copies the kit to a protected working directory. Offline validation runs before environment values are accepted. Live changes require an approved target, protected credentials, supplied local inputs, a reviewed plan or diff, explicit action approval, bounded validation and owner-aware cleanup. The skill returns an operator_execution record with real checks and evidence status.

Chapter 3 operates resources inside an existing OpenStack project. Chapter 4 establishes and maintains the Kubernetes cluster-lifecycle layer on that IaaS foundation, including the reviewed per-cluster cert-manager and private Contour/Envoy ingress declarations, bounded storage smoke test, scaling, upgrades, Argo CD path and owner-aware cleanup. Neither skill silently expands into OpenStack control-plane installation or the complete Chapter 5 production platform.

Platform integration

• Claude Code: .claude-plugin/plugin.json identifies this repository as a Claude plugin and discovers the folders under skills/.
• Codex: .codex-plugin/plugin.json packages the same skills/ directory. Each skill also has agents/openai.yaml metadata.
• Direct installation: docs/install-and-use.md describes verified checkout installation and the conditions for public-URL installation.

Data and authority boundary

The repository contains distilled, public-safe learning workflows, contracts, and exercises. It does not contain credentials, internal editorial controls, private evidence, organisation-specific topology, or a production approval. A skill may identify local evidence that is required, but it must not invent that evidence or disclose inaccessible provenance.

Validation

python3 scripts/validate_skills.py
python3 scripts/test_learning_paths.py
python3 scripts/test_operator_kits.py

The first command validates package syntax, manifests, frontmatter, references, relationships, and public-safety markers. The second runs deterministic routing and Chapter 1 to 4 coverage tests. The third verifies checksums, portable paths, script and data syntax, and both operator kits through their offline suites. These checks validate the package and its offline behaviour, not a live cloud or cluster.