best-practices
Best practices for developing with @inkcre/web-design including coding guidelines and accessibility.
发现 编程开发 相关 Skills,比较来源仓库和用途,查看适合你工作流的技能说明。
Best practices for developing with @inkcre/web-design including coding guidelines and accessibility.
Use @inkcre/web-design styling system with design tokens, SCSS mixins, and theming.
Use @inkcre/web-design Vue 3 components. Includes all 22 components with props, events, and usage examples.
Integrate @inkcre/web-design with vue-i18n for internationalization.
Integrate @inkcre/web-design with Vue Router using the adapter pattern.
Use when a Codex worklog or session recap is requested, or when auditing context usage (rot/smash) across recent Codex CLI sessions.
Generate a recap of recent Claude Code sessions with summaries of what was discussed and accomplished
Manage git worktrees for parallel branch development using custom git scripts (git-newtree, git-killtree, git-maingulp). Use when creating new worktrees, listing active worktrees, or closing/merging worktrees b...
Use this skill when the user wants to call different LLM models through OpenRouter's unified API, compare model responses, track costs and response times, or find the best model for a task. Triggers include req...
Role-based access control with RoleHandler
Working with model instances and fields
Building database queries with the Options API
Writing controller handler functions
Standards, conventions, and struct tag reference for models
conventions for new columns
Code generation for CRUD endpoints
Use when creating PRs, pushing branches, or using Graphite CLI (gt) commands. Covers gt submit, gt create, stacked PRs, and PR description formatting.
Use when navigating Shopify's World monorepo, working across multiple zones, managing sparse checkouts, or discovering code locations. Covers zone structure, manifest lookups, checkout management, and cross-zon...
Option pricing tools including Black-Scholes model, Greeks Calculation using Auto-Differentiation, and Exotic Options.
Fast Python package installer and uninstaller. Manages projects, scripts, python versions, and tools.
Techniques for 1D and 2D data interpolation using SciPy (CPU) and JAX/Interpax (GPU/Differentiable).
Essential tools for using JAX in machine learning and mathematical analysis, covering core concepts, transformations, ML specifics, control flow, and parallelism.
A comprehensive guide for developing, training, and managing neural networks using Flax NNX. Use when defining models, managing state, or writing training loops.
Solves linear systems (Ax=b) using NumPy, JAX, PyTorch, and Lineax. Covers dense, sparse, and specialized (tridiagonal) solvers.
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。