🚀 Release v1.0.0 — AI Engineering Skills & Instruction Prompts The initial production release of AI Engineering Skills & Prompts , tailored for AI coding assistants (Google Antigravity / Gemini, Cursor Rules, Claude Projects, GitHub Copilot). 🌟 Key Highlights Standard Author Metadata & Frontmatter: Every skill and documentation file now includes structured YAML frontmatter ( author , name , description , version , repository , license , created_at ) for deterministic agent consumption. MIT License with Dedicated AI Grant: Fully permissive open-source license explicitly granting all Artificial Intelligence (AI) agents, LLMs, and automated tool
Saddam Al-Slfi
What's New in v2.0.0 Chanakya - chat agent [x] On-Demand Deep Biological Evaluations : Query PubMed articles and generate structured scientific syntheses covering executive findings, assay workflows, molecular/epigenetic mechanisms, and facility takeaways. [x] Dual LLM Provider Support : Compatible with both Groq (ultra-fast Llama/Mixtral/GPT-OSS models) and Google Gemini . Pure Client-Side & Zero-Exposure Privacy [x] Direct User API Keys : Users securely provide their own API keys, stored solely within their browser's localStorage . [x] Zero Server Overhead & Zero Secret Leaks : No server-side proxies, no stored user logs, and no shared API
Das, Jyotirmoy
Source code for the multimodal LLM evaluation pipeline described in "Multimodal Large Language Models for Clinical Scar Assessment: Agreement, Bias, and Reproducibility." Implements a five-stage pipeline (image ingestion, preprocessing, multi-provider API dispatch, JSON schema validation, and Excel/CSV export) used to evaluate five MLLMs (GPT-5.4, Claude Sonnet 5, Gemini 3.1 Pro, Qwen3.7-Plus, GLM-5V-Turbo) against blinded human observer scores on the POSAS Observer Scale. Ships without patient images, API keys, or run outputs; researchers supply their own image dataset and API credentials.
Abdullah, Ahmed
Emotion-Classification: Experimental Code and Supporting Materials This repository contains the experimental code and supporting materials used for emotion classification experiments on Spanish tweets. The resource is intended to facilitate the reproducibility of the methodology, data-processing workflow, model evaluation, and statistical analysis described in the associated research article. The repository provides Python-based scripts covering the main stages of the experimental workflow, including tweet corpus preprocessing, feature extraction and vectorization, model training and evaluation, classification analysis, carbon-emission estima
Camacho Vázquez, Luis Alberto
Code, test set and evaluation results for Tiva, a retrieval-augmented chatbot that answers questions about Telkom University from the university's public web pages. Includes the deployed pipeline, the crawler, the list of source URLs, a 101-question test set with human validation, the evaluation harness, and all retrieval and end-to-end results (Gemini 3.5 Flash-Lite generator, Cohere Command A judge). Code is licensed under MIT; the test set and results under CC BY 4.0. Funded by Penelitian Strategis (Invitasi) Tematik Artificial Intelligence (AI) 2025.
Pratondo, Agus, Yafie, Haddad Alwi, Daffansyah, Muhammad Sheva Atallah
Analysis scripts accompanying the study "Management Agreement and Guideline-Citation Metadata Errors in Large Language Models for Small Renal Mass Management: A Prompt-Sensitivity Evaluation." The scripts reproduce the statistical analyses reported in the manuscript, including inter-rater reliability (Cohen's kappa), model comparisons (Cochran's Q and exact McNemar tests with Bonferroni-adjusted pairwise p values), a scenario-level Monte Carlo permutation test, and an exploratory, hypothesis-generating cluster-robust logistic regression. The study evaluated ChatGPT-5.5, Gemini 3.6 Flash, and Claude Sonnet 5 across 30 standardized small renal
çaviş, mücahit, çaviş, tuğba
Manual benchmark comparing 5 AI models (Claude Sonnet, ChatGPT default, Gemini Flash, DeepSeek unified without "Deep Thinking", and Grok Fast mode) on their free tiers, across 27 tasks spanning 5 difficulty tiers (code, reasoning, and writing), plus 15 timed speed tasks in Tier 1. Overall accuracy: Claude 27/27 (100%), DeepSeek 26/27 (96.3%), Grok 26/27 (96.3%), ChatGPT 25/27 (92.6%), Gemini 25/27 (92.6%). DeepSeek was the fastest model across all three task categories (code, reasoning, and writing). Includes full methodology, evaluation rubric, consolidated results (CSV), comparative charts, data dictionary, and documentation in both Spanish
Daboin Jiménez, Jesús David
SYDA seamlessly generates realistic synthetic test data—including structured, unstructured, PDF, and HTML—using AI and large language models. It preserves referential integrity, maintains privacy compliance, and accelerates development workflows. SYDA enables both highly regulated industries such as healthcare and banking, as well as non-regulated environments like software testing, research, and analytics, to safely simulate diverse data scenarios without exposing sensitive information.
Lingamgunta, Rama Krishna Kumar
Overview CatalystLab is a comprehensive Software-as-a-Service (SaaS) platform designed to accelerate academic research through artificial intelligence–driven ideation, literature discovery, and research planning. This release (v1.3.7) represents a production‑ready implementation of an integrated research support ecosystem that does two things simultaneously: Think - 20 structured AI brainstorming instruments help researchers pressure‑test ideas, find contradictions, explore assumptions, generate hypotheses, and discover research gaps. Discover - Every instrument run automatically extracts research concepts and searches nine free academic data
Ashif Ahmed, Shuvo
CICIoT2023 üzerinde klasik makine öğrenmesi modelleri (Lojistik Regresyon, Rastgele Orman, XGBoost) ile sıfır-atış bir büyük dil modelinin (Gemini) doğruluk, genelleme, gecikme ve maliyet açısından karşılaştırması; çapraz-tür genelleme, çapraz-küme (NSL-KDD) doğrulaması, istem ablasyonu, ikinci LLM ailesi (Llama) ve SHAP açıklanabilirliği dâhil.
Küten, Ferhat, Özalp, Ahmet Nusret
An advanced, end-to-end framework for designing, simulating, and optimizing microfluidic blood plasma separators. By leveraging Deep Learning surrogate modeling, this platform replaces slow, computationally intensive Computational Fluid Dynamics (CFD) solvers with sub-millisecond neural network predictions. This enables real-time parametric optimization via an interactive 3D/2D design dashboard powered by React and Gemini AI.
sepas1609
EcaVault est une application web progressive (PWA) conçue spécifiquement pour les inspecteurs et cadres des Établissements Cantonaux d'Assurance (ECA) suisses. Elle intègre un pipeline d'intelligence artificielle multi-modal combinant l'analyse visuelle de photos via Gemini Flash (Google), la génération de rapports institutionnels via Groq Llama-3 , et un algorithme de scoring de risque déterministe (score 0–100) enrichi par LLM. L'architecture offline-first (IndexedDB + Background Sync API) garantit l'utilisation en zone sans réseau. Le système implémente un modèle de données spécifique aux ECA (numéro de police ECAB, valeur assurée CHF, niv
Stadelmann, Sébastien
