llm-design-analysis
CommunityGuide enterprise LLM design with multi-provider
Software Engineering#cost-optimization#multi-provider#prompt-engineering#training-pipeline#qa-gates#llm-architecture#fallback-strategy
AuthorVincri126
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Enterprise teams need a rigorous, multi-provider audit workflow that surfaces architectural risks, cost overruns, schema violations, and fallback fragility before deploying desktop AI pipelines.
Core Features & Use Cases
- Architecture Protocol: Provider inventory, stage decomposition, decision-point analysis, and risk scoring keep Claude, GPT, Gemini, Groq, and Ollama stacks accountable.
- Multi-Provider Frameworks: Durable fallback chains, God Mode orchestration, circuit breakers, and cost-quality Pareto guidance ensure quality under tight latency or budget constraints.
- Training & Prompt Engineering: Distillation roadmaps, golden dataset curation, schema enforcement, and prompt versioning with self-correction loops provide production-grade quality gates.
- QA and Cost Governance: Design, implementation, and production gates with detailed checklists enable auditors to validate intent, implementation, and runtime health.
Quick Start
Ask the llm-design-analysis skill to audit my multi-provider desktop AI pipeline and return architecture risks and prioritised recommendations.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: llm-design-analysis Download link: https://github.com/Vincri126/MCO-Template/archive/main.zip#llm-design-analysis Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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