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Dépôt GitHub

case-study-series

case-study-series contient 6 skills collectées depuis lucifertrj, avec une couverture métier par dépôt et des pages de détail sur le site.

skills collectés
6
Stars
22
mis à jour
2026-04-24
Forks
7
Couverture métier
3 catégories métier · 100% classifié
explorateur de dépôts

Skills dans ce dépôt

ai-memory
Développeurs de logiciels

AI Memory is a feature that allows you to store and retrieve information from your AI assistant. This can be useful for keeping track of important information, such as your schedule, contacts, and other data.

2026-04-24
frontend-design
Développeurs web

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

2026-04-24
qdrant-vector-search
Développeurs de logiciels

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.

2026-04-24
skill-creator
Développeurs de logiciels

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

2026-04-24
ai-memory
Développeurs de logicielsAnalystes des systèmes informatiques

AI Memory is a feature that allows you to store and retrieve information from your AI assistant. This can be useful for keeping track of important information, such as your schedule, contacts, and other data.

2026-03-10
vector-search
Développeurs de logiciels

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.

2026-03-10