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: in-context-learning

Englisches Verzeichnis

Guidance for distinctive, intentional UI design, typography, visual direction, and non-template-like product interfaces.

171K
Stars
82/100
Trust
Kategorie: design-creativeAudit

All Algorithms implemented in Python

222K
Stars
82/100
Trust
Kategorie: educationAudit

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

Open-source LLM-friendly web crawler and scraper

73K
Stars
82/100
Trust
Kategorie: web-automationAudit

Review a branch or diff against repository standards and the originating spec in two independent analysis passes.

169K
Stars
86/100
Trust
Kategorie: coding-agentsAudit

Turn the current conversation and codebase context into a structured implementation spec, then publish it to the configured project issue tracker.

165K
Stars
81/100
Trust
Kategorie: coding-agentsAudit

Break a plan, spec, or conversation into independently actionable tracer-bullet tickets with explicit blocking relationships.

177K
Stars
81/100
Trust
Kategorie: coding-agentsAudit

Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.

17K
Stars
87/100
Trust
Kategorie: design-creativeAudit

Tensors and Dynamic neural networks in Python with strong GPU acceleration

101K
Stars
76/100
Trust
Kategorie: ml-automationAudit

An Open Source Machine Learning Framework for Everyone

196K
Stars
81/100
Trust
Kategorie: ml-automationAudit

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

162K
Stars
87/100
Trust
Kategorie: ml-automationAudit

Implement work from an approved spec or ticket set, run focused and full tests, invoke code review, and commit the result to the current branch.

176K
Stars
81/100
Trust
Kategorie: coding-agentsAudit