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: causal-graphs

Englisches Verzeichnis

A tool that converts codebases, SQL schemas, and other files into queryable knowledge graphs for AI coding assistants.

92K
Stars
80/100
Trust
Kategorie: developmentAudit

Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.

75K
Stars
84/100
Trust
Kategorie: rag-knowledgeAudit

✨ Innovative and open-source visualization application that transforms various data formats, such as JSON, YAML, XML and CSV into interactive graphs.

44K
Stars
86/100
Trust
Kategorie: data-analysisAudit

Build Real-Time Knowledge Graphs for AI Agents

28K
Stars
82/100
Trust
Kategorie: dataAudit

A JavaScript library aimed at visualizing graphs of thousands of nodes and edges

12K
Stars
87/100
Trust
Kategorie: data-analysisAudit

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

8.2K
Stars
86/100
Trust
Kategorie: ml-automationAudit

Uplift modeling and causal inference with machine learning algorithms

5.9K
Stars
76/100
Trust
Kategorie: ml-automationAudit

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

4.7K
Stars
76/100
Trust
Kategorie: ml-automationAudit

Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.

2.8K
Stars
73/100
Trust
Kategorie: agent-frameworksAudit

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

2.5K
Stars
83/100
Trust
Kategorie: data-analysisAudit

Python library for Representation Learning on Knowledge Graphs https://docs.ampligraph.org

2.2K
Stars
85/100
Trust
Kategorie: rag-knowledgeAudit

EdegQuake 🌋 High-performance GraphRAG inspired from LightRag written in Rust; Transform documents into intelligent knowledge graphs for superior retrieval and generation

2.0K
Stars
84/100
Trust
Kategorie: dataAudit