Skill-Verzeichnis

Wiederverwendbare Skills für AI Agents entdecken.

Durchsuche reale GitHub-Skills nach Aufgabe und prüfe Stars, Trust, Audit, Kategorie und Installationspfad vor der Verwendung.

Jede Empfehlung bleibt mit ihrem Repository, Audit und Installationspfad nachvollziehbar.

Suchergebnisse: event-forecasting

Englisches Verzeichnis

React and Next.js performance guidance for writing, reviewing, and refactoring production UI code.

30K
Stars
88/100
Trust
Kategorie: coding-agentsAudit

Conductor is an event driven agentic workflow engine providing durable and highly resilient execution engine for applications and AI Agents

32K
Stars
87/100
Trust
Kategorie: automationAudit

Multilingual speech understanding: ASR + emotion recognition + audio event detection. 50+ languages, 15x faster than Whisper, non-autoregressive.

8.6K
Stars
77/100
Trust
Kategorie: media-automationAudit

Event Driven Orchestration & Scheduling Platform for Mission Critical Applications

27K
Stars
87/100
Trust
Kategorie: agent-frameworksAudit

Dapr is a portable runtime for building distributed applications across cloud and edge, combining event-driven architecture with workflow orchestration.

26K
Stars
87/100
Trust
Kategorie: devopsAudit

Production-grade Rust-native trading engine with deterministic event-driven architecture

23K
Stars
82/100
Trust
Kategorie: sports-analyticsAudit

A Codex skill for generating minimal zine-style editorial poster prompts and images.

6.3K
Stars
83/100
Trust
Kategorie: design-creativeAudit

KEDA is a Kubernetes-based Event Driven Autoscaling component. It provides event driven scale for any container running in Kubernetes

10K
Stars
86/100
Trust
Kategorie: devopsAudit

A python library for user-friendly forecasting and anomaly detection on time series.

9.4K
Stars
86/100
Trust
Kategorie: ml-automationAudit

High-Performance Serverless event and data processing platform

5.7K
Stars
80/100
Trust
Kategorie: devopsAudit

Chronos: Pretrained Models for Time Series Forecasting

5.5K
Stars
81/100
Trust
Kategorie: ml-automationAudit

A Python toolkit/library for reality-centric machine/deep learning & data mining on partially-observed time series, with 50+ SOTA neural network models for scientific analysis tasks (imputation, classification, clustering, forecasting, anomaly detection, cleaning) on incomplete industrial irregularly-sampled multivariate TS with NaN missing values

2.0K
Stars
83/100
Trust
Kategorie: data-analysisAudit