Engineering Principles
Azure/GPT-RAG/.github/skills/engineering-principles
ai-mlOfficial
Official Provider SkillView repo
GPT-RAG architecture and implementation principles. Use for design, review, meaningful refactoring, Azure integration, security, testing, or operational changes.
Files4 files
SKILL.md19 lines
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Skill details
Versionv1.0.0
AuthorAzure
Categoryai-ml
Skill IDAzure/GPT-RAG/.github/skills/engineering-principles
Files4 files
Related skills
Architecture DecisionConducts and records a verifiable GPT-RAG architectural decision. Use when a choice alters repositories, boundaries, contracts, identity, data, deployment topology, or operation with meaningful reversal cost.Documentation ConsistencyKeeps GPT-RAG user and operator documentation aligned with shipped behavior. Use for features, configuration keys, deployment parameters, defaults, component pins, operations, or breaking changes.Multi Repo ReleasePrepares and validates GPT-RAG umbrella and multi-repository releases. Use whenever work involves release preparation, semantic versions, release branches, manifest or component pins, changelog release entries, tags, GitHub Release notes, or AI Landing Zone release alignment.Speckit AnalyzePerform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.Speckit ChecklistGenerate a custom checklist for the current feature based on user requirements.Speckit ClarifyIdentify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.