Skill UI

This framework addresses the gap between academic benchmarks and real-world production performance for LLM agents. It teaches advanced quality engineering practices, such as behavioral contract testing, adversarial testing, and statistical analysis, ensuring agents maintain reliability and robustness when deployed. It helps developers move beyond simple pass/fail rates to comprehensive capability assessment.

Deliver production-ready LLM applications, RAG systems, and multi-agent orchestration with vector databases, embedding strategies, safety controls, and observability for enterprise deployments.

Deliver production-ready LLM applications, RAG systems, and multi-agent orchestration with vector databases, embedding strategies, safety controls, and observability for enterprise deployments.

Chroma is an open-source, AI-native embedding database designed for building sophisticated LLM applications. It allows users to store high-dimensional embeddings and associated metadata, facilitating powerful vector search and full-text filtering. Ideal for implementing Retrieval-Augmented Generation (RAG) systems, semantic search, and document retrieval in local or self-hosted environments, making it perfect for open-source AI projects and prototyping.

CLIP enables general-purpose vision-language tasks through zero-shot image classification, similarity scoring, semantic search, and content moderation using pretrained contrastive embeddings without fine-tuning.

Identifies predictable context degradation patterns in large language models to diagnose failures and design resilient agents; covers lost-in-middle, poisoning, distraction, and confusion with mitigation tactics for long or complex conversations.

A specialized skill for optimizing LLM applications handling long conversations and large datasets. This guide teaches advanced context engineering techniques, addressing issues like context rot, token limits, and the lost-in-the-middle problem. Capabilities include intelligent summarization, context trimming, information prioritization, and strategic context routing to ensure critical information is retained and utilized effectively throughout the dialogue.

Helps teams choose and tune embedding models, chunking, and pipelines for vector search, covering RAG, multilingual input, and dimension-reduction scenarios.

Guides teams through reducing Exa AI search API bills by adding query caching, picking cost-effective search types, limiting result counts, deduplicating batch queries, and monitoring budget and usage alerts.

Leverages the Exa API for semantic/embeddings search, discovering similar content, or filtering by categories like companies, people, and research papers, making research and knowledge retrieval more targeted.

Defines best-practice Groq deployment with tiered model routing, middleware, streaming pipelines, and fallback chains for ultra-fast LLM inference and production monitoring when launching new Groq integrations.

Last30days lets you research any topic across Reddit, X, YouTube, TikTok, Instagram, Hacker News, Polymarket and the open web by planning multi-platform search queries and falling back to Gemini/OpenAI for missing sources; it composes briefings, tracks recency, and saves citations.