sota-llm-engineering

What problem does it solve?

This Skill ensures the engineering and auditing of LLM-powered features are done according to the latest 2026 standards, enhancing build quality and security.

Core Features & Use Cases

• LLM Feature Engineering: Defines best practices for building LLM features with measurable, grounded, bounded, and observable outcomes.
• Audit Mode: Identifies and reports quality violations with severity ratings.
• Eval Suite Development: Provides guidelines for creating comprehensive eval suites to ensure feature quality.
• Prompt and Context Engineering: Offers strategies for structuring prompts and managing context budgets.
• RAG and Retrieval: Details how to design and evaluate RAG systems for reliable information retrieval.
• Agent and Tool Use: Establishes guidelines for designing and managing agents and tools used in LLM workflows.
• Production Engineering: Covers best practices for model selection, cost engineering, and observability in production environments.
• Data Lifecycle: Provides guidelines for dataset curation, feedback loops, and embedding migration.
• Use Case: Imagine you are developing a chatbot that provides financial advice. Use this Skill to ensure that the chatbot's advice is grounded in relevant information, that the system prompts are secure and effective, and that the model selection is appropriate for the task.

Quick Start

Run the sota-llm-engineering skill to start building or auditing an LLM feature.