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: beam

Englisches Verzeichnis

Beam: Scalable Confidential Cryptocurrency. Leading the way to Confidential DeFi

722
Stars
73/100
Trust
Kategorie: web3-analyticsAudit

Apache Beam is a unified programming model for Batch and Streaming data processing.

8.6K
Stars
85/100
Trust
Kategorie: data-analysisAudit

A type-safe Haskell SQL library

625
Stars
66/100
Trust
Kategorie: data-analysisAudit

AI suite powered by state-of-the-art models and providing advanced AI/AGI functions. Includes AI personas, AGI functions, world-class Beam multi-model chats, text-to-image, voice, response streaming, code highlighting and execution, PDF import, presets for developers, much more. Deploy on-prem or in the cloud.

7.0K
Stars
84/100
Trust
Kategorie: agent-frameworksAudit

Testable, composable, and adapter based Elixir email library for devs that love piping.

2.0K
Stars
85/100
Trust
Kategorie: productivity-automationAudit

Kubernetes operator for managing the lifecycle of Apache Flink and Beam applications.

225
Stars
70/100
Trust
Kategorie: devopsAudit

Connectionist Temporal Classification (CTC) decoding algorithms: best path, beam search, lexicon search, prefix search, and token passing. Implemented in Python.

836
Stars
66/100
Trust
Kategorie: media-automationAudit

Detect and analyze geometric clashes in BIM models. Identify MEP, structural, and architectural conflicts before construction.

282
Stars
61/100
Trust
Kategorie: automationAudit

Classify BIM elements using AI and standard classification systems. Map elements to UniFormat, MasterFormat, OmniClass, and CWICR codes.

282
Stars
63/100
Trust
Kategorie: coding-agentsAudit

An AI agent skill for creating animation-rich HTML presentations from scratch or by converting PowerPoint files.

11
Stars
65/100
Trust
Kategorie: presentationAudit

基于seq2seq模型的简单对话系统的tf实现,具有embedding、attention、beam_search等功能,数据集是Cornell Movie Dialogs

335
Stars
59/100
Trust
Kategorie: support-automationAudit