Awesome List Updates on Jun 23, 2025
9 awesome lists updated today.
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1. Awesome Newsletters
Marketing / Svelte
- Geekout Newsletter - latest social media platform news, tips, tools, and new features
2. Awesome Esolangs
Languages
- Schoenberg - The MIDI Esoteric Programming Language.
3. Awesome Angular
- angular-mcp-server (⭐1) - A Model Context Protocol (MCP) server that provides comprehensive access to Angular documentation, enabling AI assistants to search and retrieve Angular-related information with intelligent relevance scoring.
HTTP / Google Developer Experts
- ngx-http-resilience (⭐1) - Angular HttpInterceptors that provide resiliency capabilities.
Mixed utilities / Google Developer Experts
- reactive-kit (⭐1) - A lightweight set of utilities that make reactive Angular apps more enjoyable and less boilerplate-heavy. Works great alongside
ngxtension.
4. Awesome Zig
Concurrency
- floscodes/coroutinez (⭐2) - Small runtime for running tasks using coroutines.
5. Awesome Firebase Genkit
Client Libraries / Dart - Official
dart-client-for-genkit- A type-safe Dart client library for calling Genkit flows with streaming support, authentication, and comprehensive error handling.
Articles / Dart - Official
- Dart Client for Genkit: Call Genkit Flows from Flutter/Dart - A comprehensive guide to using the Dart client library for calling Genkit flows from Flutter and Dart applications with streaming support and type safety.
6. Awesome Vue
Resources / Tutorials
Components & Libraries / UI Components
- vue-snap (⭐164) - 🌿 Modern and lightweight Vue 3 Carousel powered by CSS Scroll Snap.
Components & Libraries / Scaffold
- monorepo-template (⭐2) - 🗂️ Vue 3 monorepo template with pnpm, Nx, Vite, Tailwind CSS, Storybook, TypeScript, and ready-to-use shared libraries.
7. Awesome Keycloak
Articles
Community Extensions
8. Awesome Rust
Applications
- Edit (⭐12k) - A simple editor for simple needs.
Libraries / Data streaming
- swim-rust (⭐345) [swim-rust] - Self-contained distributed software platform for building stateful, massively real-time streaming applications.
9. Awesome Agi Cocosci
Problem Solving / Human-Level Problem Solving
- Beyond imitation: Zero-shot task transfer on robots by learning concepts as cognitive programs - Science Robotics, 2019. [All Versions]. Humans can infer concepts from image pairs and apply those in the physical world in a completely different setting, enabling tasks like IKEA assembly from diagrams. If robots could represent and infer high-level concepts, then it would notably improve their ability to understand our intent and to transfer tasks between different environments. To that end, the authors introduce a computational framework that replicates aspects of human concept learning. Concepts are represented as programs on a computer architecture consisting of a visual perception system, working memory, and action controller. The instruction set of this cognitive computer has commands for parsing a visual scene, directing gaze and attention, imagining new objects, manipulating the contents of a visual working memory, and controlling arm movement. Inferring a concept corresponds to inducing a program that can transform the input to the output. Some concepts require the use of imagination and recursion. Previously learned concepts simplify the learning of subsequent, more elaborate concepts and create a hierarchy of abstractions. The authors demonstrate how a robot can use these abstractions to interpret novel concepts presented to it as schematic images and then apply those concepts in very different situations. By bringing cognitive science ideas on mental imagery, perceptual symbols, embodied cognition, and deictic mechanisms into the realm of machine learning, this work brings researchers closer to the goal of building robots that have interpretable representations and common sense.
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