Direktori skill

Temukan skill yang dapat digunakan kembali untuk AI agents.

Cari skill GitHub nyata berdasarkan tugas lalu periksa stars, trust, audit, kategori, dan jalur pemasangan sebelum digunakan.

Setiap rekomendasi tetap terhubung dengan repositori, audit, dan jalur pemasangannya.

Hasil pencarian: causal-reasoning

Direktori bahasa Inggris

Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.

30K
Stars
87/100
Kepercayaan
Kategori: rag-knowledgeAudit

📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG

34K
Stars
80/100
Kepercayaan
Kategori: rag-knowledgeAudit

This skill encodes Emil Kowalski's philosophy on UI polish, component design, animation decisions, and the invisible details that make software feel great.

13K
Stars
87/100
Kepercayaan
Kategori: design-creativeAudit

Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.

16K
Stars
79/100
Kepercayaan
Kategori: rag-knowledgeAudit

给纯文本 LLM agent 装上眼睛:图片问答、OCR、截图分析、视觉定位等一套视觉工具箱 + skill,并可无缝接入 Codex、Claude Code、OpenCode、Pi | Give text-only LLM agents vision: image Q&A, OCR, screenshot understanding, visual grounding, image-to-SVG - a vision toolkit & skill, with drop-in integration for Codex, Claude Code, OpenCode, Pi

1.1K
Stars
85/100
Kepercayaan
Kategori: utilityAudit

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
Kepercayaan
Kategori: ml-automationAudit

28 eval-informed mental models and critical-thinking skills for Claude Code, GitHub Copilot, Codex, Cursor, and other Agent Skills-compatible tools

941
Stars
84/100
Kepercayaan
Kategori: utilityAudit

Uplift modeling and causal inference with machine learning algorithms

5.9K
Stars
76/100
Kepercayaan
Kategori: 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
Kepercayaan
Kategori: ml-automationAudit

Implement a reasoning LLM in PyTorch from scratch, step by step

4.5K
Stars
80/100
Kepercayaan
Kategori: ml-automationAudit

Canonical source and governance toolkit for Zhijian AI public Agent Skills

292
Stars
75/100
Kepercayaan
Kategori: utilityAudit