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: distance

英語版ディレクトリ

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

18K
Stars
87/100
信頼
カテゴリ: design-creative監査

A geospatial analytics skill for AI agents like Claude, Codex, and Copilot, enabling map-based queries on PostGIS, BigQuery, Snowflake.

571
Stars
84/100
信頼
カテゴリ: data監査

Run a 5-dimension expert design review on any HTML artifact in the project — Philosophy / Visual hierarchy / Detail / Functionality / Innovation, each scored 0–10. Outputs a single self-contained HTML report with a radar chart, evidence-backed scores, and three lists: Keep / Fix / Quick-wins. Use when the brief asks for a "design review", "design critique", "5 维度评审", "design audit", or "what's wrong with my design".

90K
Stars
80/100
信頼
カテゴリ: security監査

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
信頼
カテゴリ: data-analysis監査

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

34K
Stars
80/100
信頼
カテゴリ: research監査

Distance-based Analysis of DAta-manifolds in python

149
Stars
68/100
信頼
カテゴリ: data-analysis監査

[Deprecated; use POT instead] Fast EMD for Python: a wrapper for Pele and Werman's C++ implementation of the Earth Mover's Distance metric

492
Stars
69/100
信頼
カテゴリ: geo-science監査

Build, migrate, theme, drill down, and validate reusable Three.js 3D geographic maps and Earth View entrances for Vue or web dashboards. Use when Codex is asked to create or modify a pure Three.js globe, province-level, all-China, or world 3D maps; transition from an Earth View into the existing China map; switch map boundaries between provinces, country scope, world scope, city scope, or district scope; add hierarchical drilldown from world to country, China to province, province to city, city to district/county; replace GeoJSON, labels, scatter points, fly lines, terrain textures, or chase-light paths; derive a whole map color system from one theme color; or preserve an existing dark HUD-style 3D map visual across new regions.

475
Stars
66/100
信頼
カテゴリ: design-creative監査

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

282
Stars
61/100
信頼
カテゴリ: automation監査

AI-powered PPT generation — 40,000+ style combinations, narrative-driven, design-intelligent, AI images, fully editable .pptx. Three modes: Build (default) + VI Build + FreeStyle (quick draft). 8 goal-type layouts, 35 moods, README parsing, size-aware image assignment, 3 structurally-different build.py proposals, brand compliance. Engines: Seedream, GPT Image, DALL-E, Wanx, Kimi.

240
Stars
64/100
信頼
カテゴリ: security監査

Official PyTorch implementation of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image", ICCV 2019

865
Stars
65/100
信頼
カテゴリ: robotics-iot監査

Fast Incremental Euclidean Distance Fields for Online Motion Planning of Aerial Robots

802
Stars
65/100
信頼
カテゴリ: robotics-iot監査