技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: optimal-transport

英文目录

React and Next.js performance guidance for writing, reviewing, and refactoring production UI code.

30K
Stars
88/100
信任
分类: coding-agents审计

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
信任
分类: design-creative审计

Firefox user.js for optimal privacy and security. Your favorite browser, but better.

11K
Stars
85/100
信任
分类: legal-compliance审计
POT80

POT : Python Optimal Transport

2.8K
Stars
80/100
信任
分类: ml-automation审计

A QoS-based scheduling system brings optimal layout and status to workloads such as microservices, web services, big data jobs, AI jobs, etc.

1.7K
Stars
85/100
信任
分类: devops审计

Audio generation skill — jingles, beds, voiceover, and sound effects. Routes music requests to Suno V5 / Udio / Lyria, speech to MiniMax TTS / FishAudio / ElevenLabs V3, and SFX to ElevenLabs SFX or AudioCraft. Output is one MP3/WAV file saved to the project folder.

90K
Stars
69/100
信任
分类: design-creative审计

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

51K
Stars
68/100
信任
分类: design-creative审计

Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

34K
Stars
77/100
信任
分类: data-analysis审计

Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.

34K
Stars
70/100
信任
分类: research审计

Optimal Reciprocal Collision Avoidance (C#)

844
Stars
71/100
信任
分类: robotics-iot审计

A toolkit to create optimal Production-readyRetrieval Augmented Generation(RAG) setup for your data

1.5K
Stars
73/100
信任
分类: rag-knowledge审计