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Agent Skills

共 5368 个 Skill，按仓库 star 排序。分类自动生成，仅供参考。

全部AI 与智能体1707文档与办公662前端开发572测试528项目与协作342数据库与数据300DevOps 与云291科研289代码质量与审查235安全225浏览器自动化217
r-cran-extrachecks
posit-dev/skills531

r-cran-extrachecks

Prepare R packages for CRAN submission by checking for common ad-hoc requirements not caught by devtools::check(). Use when: (1) Preparing a package for first CRAN release, (2) Preparing a package update for CRAN resubmission, (3) Reviewing a package to ensure CRAN compliance, (4) Responding to CRAN reviewer feedback. Covers documentation requirements, DESCRIPTION field standards, URL validation, examples, and administrative requirements.

AI 与智能体

r-cran-status
posit-dev/skills531

r-cran-status

Look up an R package's live status on cran.r-project.org - submission/review state (queue, human review, waiting, archived, past version's fate) or R CMD check results (OK/NOTE/WARN/ERROR per platform). Use for "what's the CRAN status of X", "did X get accepted/rejected", "is X passing CRAN checks", "when was version Y archived".

AI 与智能体

release-post
posit-dev/skills531

release-post

Create professional package release blog posts following Tidyverse or Shiny blog conventions. Use when the user needs to: (1) Write a release announcement blog post for an R or Python package for tidyverse.org or shiny.posit.co, (2) Transform NEWS/changelog content into blog format, (3) Generate acknowledgments sections with contributor lists, (4) Format posts following specific blog platform requirements. Supports both Tidyverse (hugodown) and Shiny (Quarto) blog formats with automated contributor fetching and comprehensive style guidance.

AI 与智能体

review-testing
posit-dev/skills531

review-testing

Review test code for quality, design, and completeness after implementing a feature or fixing a bug. Use when the user asks to "review my tests", "check my test quality", "are these tests good enough", "review testing", or after completing a feature implementation that includes tests. Also use when tests feel brittle, flaky, or superficial. Cross-references production code to find coverage gaps.

测试

r-lifecycle
posit-dev/skills531

r-lifecycle

Guidance for managing R package lifecycle according to tidyverse principles using the lifecycle package. Use when: (1) Setting up lifecycle infrastructure in a package, (2) Deprecating functions or arguments, (3) Renaming functions or arguments, (4) Superseding functions, (5) Marking functions as experimental, (6) Understanding lifecycle stages (stable, experimental, deprecated, superseded), or (7) Writing deprecation helpers for complex scenarios.

DevOps 与云

r-mirai
posit-dev/skills531

r-mirai

Help users write correct R code for async, parallel, and distributed computing using mirai. Use when users need to run R code asynchronously or in parallel, write mirai code with correct dependency passing, set up parallel workers, convert from future or parallel, use mirai_map, integrate with Shiny or promises, or configure cluster/HPC computing.

AI 与智能体

r-package-development
posit-dev/skills531

r-package-development

R package development with devtools, testthat, and roxygen2. Use when the user is working on an R package, running tests, writing documentation, or building package infrastructure.

测试

r-testthat
posit-dev/skills531

r-testthat

Best practices for writing R package tests with testthat version 3+. Use this skill when writing or organizing tests for an R package or when improving existing tests that use testthat. It covers test structure and expectations, self-sufficient test design, proper cleanup with withr, fixtures, mocking external dependencies, snapshot testing, and BDD-style describe/it patterns.

测试

r-tidyverse-style
posit-dev/skills531

r-tidyverse-style

Use when the user asks to review or clean up R code for tidyverse style, standardize formatting or names, remove redundant comments or wrappers, or make a behavior-preserving style pass. Also use when writing substantial new R package code if the user requests tidyverse style or the package already follows it. Not for routine small edits or general correctness, security, or test-quality reviews.

测试

shiny-bslib
posit-dev/skills531

shiny-bslib

Build modern Shiny dashboards and applications using bslib (Bootstrap 5). Use when creating new Shiny apps, modernizing legacy apps (fluidPage, fluidRow/column, tabsetPanel, wellPanel, shinythemes), or working with bslib page layouts, grid systems, cards, value boxes, navigation, sidebars, filling layouts, theming, accordions, tooltips, popovers, toasts, or bslib inputs. Assumes familiarity with basic Shiny.

AI 与智能体

shiny-bslib-theming
posit-dev/skills531

shiny-bslib-theming

Advanced theming for Shiny apps using bslib and Bootstrap 5. Use when customizing app appearance with bs_theme(), Bootswatch themes, custom colors, typography, brand.yml integration, Bootstrap Sass variables, custom Sass/CSS rules, dark mode and color modes, dynamic theme switching, real-time theming, theme inspection, or making R plots match the app theme with thematic.

前端开发

working-on
posit-dev/skills531

working-on

Set a tracking document as the source of truth for the current feature or task. Use when starting work on a feature, bug fix, or multi-step task that benefits from a persistent record of decisions, discoveries, and progress. Keeps the document updated as work proceeds.

AI 与智能体

browser-search
Johell1NS/browser-search528

browser-search

Multi-engine web search (SearXNG) + browsing/scraping (Camofox, CloakBrowser). Use whenever you need to do web research.

浏览器自动化

administering-linux
ancoleman/ai-design-components526

administering-linux

Manage Linux systems covering systemd services, process management, filesystems, networking, performance tuning, and troubleshooting. Use when deploying applications, optimizing server performance, diagnosing production issues, or managing users and security on Linux servers.

前端开发

ai-data-engineering
ancoleman/ai-design-components526

ai-data-engineering

Data pipelines, feature stores, and embedding generation for AI/ML systems. Use when building RAG pipelines, ML feature serving, or data transformations. Covers feature stores (Feast, Tecton), embedding pipelines, chunking strategies, orchestration (Dagster, Prefect, Airflow), dbt transformations, data versioning (LakeFS), and experiment tracking (MLflow, W&B).

前端开发

architecting-data
ancoleman/ai-design-components526

architecting-data

Strategic guidance for designing modern data platforms, covering storage paradigms (data lake, warehouse, lakehouse), modeling approaches (dimensional, normalized, data vault, wide tables), data mesh principles, and medallion architecture patterns. Use when architecting data platforms, choosing between centralized vs decentralized patterns, selecting table formats (Iceberg, Delta Lake), or designing data governance frameworks.

前端开发

architecting-networks
ancoleman/ai-design-components526

architecting-networks

Design cloud network architectures with VPC patterns, subnet strategies, zero trust principles, and hybrid connectivity. Use when planning VPC topology, implementing multi-cloud networking, or establishing secure network segmentation for cloud workloads.

前端开发

architecting-security
ancoleman/ai-design-components526

architecting-security

Design comprehensive security architectures using defense-in-depth, zero trust principles, threat modeling (STRIDE, PASTA), and control frameworks (NIST CSF, CIS Controls, ISO 27001). Use when designing security for new systems, auditing existing architectures, or establishing security governance programs.

前端开发

assembling-components
ancoleman/ai-design-components526

assembling-components

Assembles component outputs from AI Design Components skills into unified, production-ready component systems with validated token integration, proper import chains, and framework-specific scaffolding. Use as the capstone skill after running theming, layout, dashboard, data-viz, or feedback skills to wire components into working React/Next.js, Python, or Rust projects.

前端开发

building-ai-chat
ancoleman/ai-design-components526

building-ai-chat

Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provides battle-tested components from leading AI products with accessibility and performance built in.

前端开发

building-ci-pipelines
ancoleman/ai-design-components526

building-ci-pipelines

Constructs secure, efficient CI/CD pipelines with supply chain security (SLSA), monorepo optimization, caching strategies, and parallelization patterns for GitHub Actions, GitLab CI, and Argo Workflows. Use when setting up automated testing, building, or deployment workflows.

前端开发

building-clis
ancoleman/ai-design-components526

building-clis

Build professional command-line interfaces in Python, Go, and Rust using modern frameworks like Typer, Cobra, and clap. Use when creating developer tools, automation scripts, or infrastructure management CLIs with robust argument parsing, interactive features, and multi-platform distribution.

前端开发

building-forms
ancoleman/ai-design-components526

building-forms

Builds form components and data collection interfaces including contact forms, registration flows, checkout processes, surveys, and settings pages. Includes 50+ input types, validation strategies, accessibility patterns (WCAG 2.1), multi-step wizards, and UX best practices. Provides decision trees from data type to component selection, validation timing guidance, and error handling patterns. Use when creating forms, collecting user input, building surveys, implementing validation, designing multi-step workflows, or ensuring form accessibility.

前端开发

building-tables
ancoleman/ai-design-components526

building-tables

Builds tables and data grids for displaying tabular information, from simple HTML tables to complex enterprise data grids. Use when creating tables, implementing sorting/filtering/pagination, handling large datasets (10-1M+ rows), building spreadsheet-like interfaces, or designing data-heavy components. Provides performance optimization strategies, accessibility patterns (WCAG/ARIA), responsive designs, and library recommendations (TanStack Table, AG Grid).

前端开发