Skill ディレクトリ

AI Agent のための再利用可能な Skill を見つける。

タスクで実際の GitHub Skill を検索し、利用前に Stars、Trust、監査、カテゴリ、インストール経路を確認できます。

すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。

検索結果: incremental-computation

英語版ディレクトリ

Incremental engine for long horizon agents 🌟 Star if you like it!

10K
Stars
82/100
信頼
カテゴリ: rag-knowledge監査

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

9.0K
Stars
86/100
信頼
カテゴリ: ml-automation監査

node of the decentralized oracle network, bridging on and off-chain computation

8.2K
Stars
75/100
信頼
カテゴリ: web3-analytics監査

esProc SPL is a JVM-based programming language designed for structured data computation, serving as both a data analysis tool and an embedded computing engine.

4.7K
Stars
83/100
信頼
カテゴリ: data-analysis監査

Apache Linkis builds a computation middleware layer to facilitate connection, governance and orchestration between the upper applications and the underlying data engines.

3.4K
Stars
83/100
信頼
カテゴリ: data-analysis監査

LakeSoul is an end-to-end, realtime and cloud native Lakehouse framework with fast data ingestion, concurrent update and incremental data analytics on cloud storages for both BI and AI applications.

3.2K
Stars
83/100
信頼
カテゴリ: data-analysis監査

The Feldera Incremental Computation Engine

1.9K
Stars
72/100
信頼
カテゴリ: data-analysis監査

Fast symbolic computation, code generation, and nonlinear optimization for robotics

1.6K
Stars
84/100
信頼
カテゴリ: robotics-iot監査

An Agent Skill helping you to optimize Xcode incremental and clean builds by running benchmarks and optimizing build settings.

1.1K
Stars
80/100
信頼
カテゴリ: agent-skills監査

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

34K
Stars
77/100
信頼
カテゴリ: data-analysis監査

Use when the user needs something that ships outside cognee core — community database adapters (Qdrant, Milvus, Weaviate, Redis, Pinecone, FalkorDB, Memgraph, DuckDB, NetworkX, …), data-source connectors (Slack, Gmail, Notion, Confluence, Google Drive), custom tasks/pipelines/retrievers (Exa, ScrapeGraph, codify), Keywords AI observability — or wants to contribute a package to the cognee-community repo.

30K
Stars
74/100
信頼
カテゴリ: research監査

Hummingbird compiles trained ML models into tensor computation for faster inference.

3.5K
Stars
74/100
信頼
カテゴリ: ml-automation監査