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: behaviour-trees

Englisches Verzeichnis

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
Trust
Kategorie: rag-knowledgeAudit

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
Trust
Kategorie: ml-automationAudit

A curated collection of reusable AI agent skills following the Agent Skills open format, designed to extend coding agents with specialized capabilities.

181
Stars
72/100
Trust
Kategorie: coding-agentsAudit

🌱 Construct Merkle Trees and verify proofs in JavaScript. By @miguelmota

1.2K
Stars
74/100
Trust
Kategorie: web3-analyticsAudit

Ultra-fast matching engine written in Java based on LMAX Disruptor, Eclipse Collections, Real Logic Agrona, OpenHFT, LZ4 Java, and Adaptive Radix Trees.

2.6K
Stars
70/100
Trust
Kategorie: financeAudit

🦞 Official plugin for OpenClaw that exports agent traces to Opik. See and monitor agent behaviour, cost, tokens, errors and more.

620
Stars
73/100
Trust
Kategorie: devopsAudit

Python implementation of behaviour trees.

611
Stars
66/100
Trust
Kategorie: robotics-iotAudit

Rust implementation of behavior trees for deterministic AI (now with Python bindings)

550
Stars
72/100
Trust
Kategorie: robotics-iotAudit

Local-only web GUI for inspecting agent skills (SKILL.md) across user, project, plugin, cache, and marketplace sources

65
Stars
69/100
Trust
Kategorie: utilityAudit

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

1.9K
Stars
72/100
Trust
Kategorie: ml-automationAudit

Golang data structures — slices (internals, capacity growth, preallocation, slices package), maps (internals, hash buckets, maps package), arrays, container/list/heap/ring, strings.Builder vs bytes.Buffer, generic collections, pointers (unsafe.Pointer, weak.Pointer), and copy semantics. Use when choosing or optimizing Go data structures, implementing generic containers, using container/ packages, unsafe or weak pointers, or questioning slice/map internals.

3.0K
Stars
73/100
Trust
Kategorie: design-creativeAudit

A framework for parsing and transforming text in Markdown format written in Swift 6 for macOS, iOS, and Linux. The syntax is based on the CommonMark specification. The framework defines an abstract syntax for Markdown, provides a parser for parsing strings into abstract syntax trees, and comes with generators for HTML and attributed strings.

209
Stars
70/100
Trust
Kategorie: document-processingAudit