# brand-guidelines: Let AI Agent Automatically Apply Anthropic Official Brand Specifications
`brand-guidelines` is an official Anthropic Skills example that writes brand colors (#141413, #d97757, etc.) and Poppins/Lora font rules into `SKILL.md`, enabling Agents to automatically align with visual specifications when generating PPTs, documents, and HTML. Based on verification against the official `SKILL.md` and the repository README, this article introduces its positioning, color palette details, installation methods for Cursor/Claude Code/Claude.ai, typical prompts, as well as reusable patterns and precautions for building enterprise self-built design specification Skills.
Read More### 正式译法（符合技术文章标题规范）： # Algorithmic Art: Integrate p5.js Algorithmic Art into AI Programming Assistants with Agent Skill
### Official Creative Skill: algorithmic-art from Anthropic This skill generates interactive algorithmic art based on p5.js and seed randomization. After verifying against the official SKILL.md document, this article explains its two-stage workflow of "algorithmic philosophy + HTML finished product", the constraints of the viewer.html template, as well as the installation methods and typical prompt words in Cursor, Claude Code and Claude.ai. It is suitable for developers who want to quickly create generative art or learn creative Agent Skills.
Read More# unit-test-generator: Let AI Agent Automatically Generate Unit Tests According to Specifications
The unit-test-generator is a community example Skill in the JackyST0/awesome-agent-skills repository. It standardizes the workflow of "identifying code, analyzing boundaries, selecting frameworks, and generating test cases" via SKILL.md, and supports multiple programming languages including Python, JavaScript/TypeScript, Java, Go, Rust, etc., as well as testing frameworks such as pytest, Jest, JUnit, etc. This article introduces its positioning, core capabilities, installation methods on platforms like Cursor/Codex, official divide function examples, applicable scenarios such as test case supplementation and team specification implementation, as well as usage notes.
Read MoreCode Review: Equip AI Programming Assistants with "Standardized Code Review Workflows"
code-review is an official sample Skill built into the awesome-agent-skills repository. It defines a unified code review process for AI programming tools such as Cursor, Claude Code, and Copilot via SKILL.md. It covers five types of checks including syntax, logic, security, performance and style, and outputs a standard report containing problem lists, improvement suggestions and three scores. This article introduces its origin, core capabilities, one-click/manual installation methods, typical usage and applicable scenarios, to help developers standardize AI-assisted code review quickly.
Read More### 正式译法（适配技术文档场景）： Setting up CI: Let AI Agents Help You Build GitHub Actions CI/CD Pipelines
# setup-ci from awesome-cursor-skills: A beginner-friendly DevOps skill for GitHub Actions This skill detects Node.js, Python, Go and other projects via the SKILL.md specification, then generates a `ci.yml` workflow that includes linting, testing, type checking and optional deployment. It emphasizes the use of `npm ci`, dependency caching and secret security best practices. This article covers installation (deploying to `.cursor/skills/`), typical usage and precautions, and is ideal for quickly setting up CI/CD for new projects.
Read MoreFour Perspectives on One PR: Practical Combat of Parallel Code Review Skills
### 翻译版本1（正式技术文档风格）： `parallel-code-review` is a Cursor-Native Skill in the `awesome-cursor-skills` repository. It leverages the Task tool to launch four read-only explore sub-agents simultaneously to review the same code diff across four dimensions: security, performance, correctness, and readability, before the main agent deduplicates and consolidates the results into a hierarchical report. After verifying against the official `SKILL.md`, this article introduces the installation methods (via `.cursor/skills/` or `npx skills`), four-step workflow (scope the changes, conduct parallel review, synthesize the report, and optional repair), as well as applicable scenarios and limitations. ### 翻译版本2（更贴合开源社区表述习惯）： `parallel-code-review` is a Cursor-native skill hosted in the `awesome-cursor-skills` repo. It uses the Task tool to spin up four read-only explore sub-agents at once to audit the same code diff from four perspectives: security, performance, correctness, and readability. The main agent will then deduplicate and merge the feedback into a tiered report. This article first cross-checks with the official `SKILL.md`, then walks through the installation steps (either via `.cursor/skills/` directory or `npx skills`), the four-stage workflow (select the changes to review, run parallel audits, compile the final report, and apply fixes optionally), plus the applicable use cases and current constraints of the skill.
Read MoreExtracting Skills from Repeated Patterns: Detailed Explanation of the Meta-skill building-skills-from-patterns
### 正式翻译（符合技术文档语境）： `building-skills-from-patterns` is a meta-skill in the `awesome-cursor-skills` repository. It teaches the Cursor Agent to recognize recurring multi-step workflows and save them as `SKILL.md` files under the `.cursor/skills/` directory. This article introduces its trigger conditions, four-step workflow, division of labor with Rules and Hooks, as well as installation methods and typical use cases, helping developers advance from "repeatedly dictating workflows" to "building reusable Skills on their own".
Read More# Systematic Debugging: Integrate Structured Debugging Methodology into Skill to Enable AI Troubleshooting Without Blind Guesses
### 正式翻译： The `systematic-debugging` repository comes from `awesome-cursor-skills`. It will write the five-step debugging process of reproduction, isolation, hypothesis, verification and repair into `SKILL.md`, covering git bisect, binary search and minimal reproduction. This article introduces its origin, core capabilities, installation methods in AI programming tools such as Cursor, as well as typical usages such as automatic triggering and explicit invocation via `/systematic-debugging`, helping developers constrain Agents to troubleshoot based on evidence rather than randomly modifying code.
Read More# 翻译结果： Architecture Decision Records: Documenting Technical Decisions with Agent Skill
### Translation: Let me introduce the *architecture-decision-records* skill included in awesome-cursor-skills: it teaches AI Agents to document technical decisions in accordance with ADR specifications, covering their backgrounds, alternative options and justifications. The skill covers when to write ADRs, template structures, a six-step workflow, installation methods and typical prompt examples, helping teams turn architectural governance from verbal agreements into retrievable decision logs.
Read MoreAdding E2E Tests: Building Playwright End-to-End Tests from Scratch with Agent Skill
### 正式翻译： # Adding E2E Tests from awesome-cursor-skills: Teach AI Agents to Build Playwright E2E Testing from Scratch This tutorial covers end-to-end setup with Playwright: installing dependencies, configuring `playwright.config.ts`, writing smoke tests and Page Objects, supplementing npm scripts and `.gitignore`, integrating GitHub Actions CI, and emphasizes best practices for `data-testid` and Playwright Codegen. It explains the positioning of this skill, its differences from webapp-testing, installation methods for Cursor/Claude Code, and a seven-step implementation workflow, making it suitable for frontend and full-stack projects that have not yet adopted E2E testing.
Read MoreAdding Auth: Enabling AI Agents to Integrate with Auth.js Authentication via Standard Procedures
*adding-auth* has been included in awesome-cursor-skills. The integration of Auth.js v5 with Next.js App Router has been organized into an 8-step workflow: dependency installation, setting up AUTH_SECRET, auth.ts configuration, OAuth setup, Route Handler implementation, login UI and route protection, and optional database Adapter. Verified against the official SKILL.md and Auth.js documentation, this article introduces the installation method and typical usage, suitable for web developers who need to quickly integrate OAuth and sessions.
Read More1. Auditing-Security: Systematically Audit Code Repositories with Agent Skill
### Introduction to awesome-cursor-skills Selected Skill auditing-security: Write review steps including OWASP Top 10, key leakage, injection and dependency vulnerabilities into SKILL.md for agents such as Cursor to conduct systematic audits of business code according to the 7-step checklist. The content covers installation methods, prompt examples, and the complementary relationship with Skill supply chain security tools such as SkillScan.
Read More# cloudflare-deploy: Let AI Agents Deploy Applications to Cloudflare Edge Network
`cloudflare-deploy` is an Agent Skill under the OpenAI openai/skills curated directory. It guides AI Agents to complete full-stack deployments on Cloudflare, including Workers, Pages, and services like KV/D1/R2, via decision trees and reference documents. This article verifies the official SKILL.md, introduces its differences from vercel-deploy, the installation methods for Codex/Cursor, the Wrangler authentication process and typical deployment commands, which is suitable for developers who need edge Serverless and multi-cloud deployments.
Read More# figma-implement-design: Official OpenAI Skill that 1:1 restores Figma design drafts to production-grade code
**figma-implement-design** is an OpenAI-curated Agent Skill that works with the Figma MCP to translate design nodes into deliverable UI code within repositories. This article introduces its seven-step workflow, boundaries with other Skills such as figma-use, prerequisites for the MCP, as well as installation and typical usage in tools like Cursor (/add-plugin figma) and Codex ($skill-installer), helping developers shorten the Design-to-Code iteration cycle.
Read MoreOpenAI Official Security-Best-Practices: Performing Security Reviews of AI According to Languages and Frameworks
OpenAI has provided the `security-best-practices` Skill in the `curated` directory of the openai/skills repository. It includes 10 security specifications for common frameworks in Python, JavaScript/TypeScript and Go, and supports secure-by-default coding, passive inspection and structured security reporting. This article introduces its workflow, references library, Codex/Cursor installation methods and typical prompts, to help developers embed verifiable security review capabilities into AI-assisted programming.
Read More### 版本1（面向技术用户，贴合原文语境）： `vercel-deploy`: Let AI Agents Deploy Projects to Vercel with One Click ### 版本2（更地道的技术文档译法）： `vercel-deploy`: Enable AI Agents to One-Click Deploy Projects to Vercel
Vercel-deploy is a Vercel deployment Skill in the OpenAI Skills curated directory, which guides AI Agents to one-click deploy applications to Vercel. It uses preview deployment by default; prioritizes Vercel CLI, and automatically downgrades to the deploy.sh script when not logged in, and can return previewUrl and claimUrl without prior account configuration. It supports automatic detection of frameworks such as Next.js, Nuxt, Astro, etc., and is applicable to tools such as Cursor, Codex CLI, and Claude Code.
Read MoreDrive Real Browsers via Terminal: Getting Started with OpenAI's Official Playwright Skill
OpenAI's featured Skill "playwright" wraps the Playwright Agent CLI into a terminal browser automation workflow: opening pages, taking snapshots to obtain element references, filling forms and clicking, taking screenshots, and debugging with Trace. Verified based on the official SKILL.md, this article introduces the installation methods (Codex skill-installer, Cursor .cursor/skills), the usage of the wrapper script, typical command examples, as well as precautions such as re-snapshotting when refs fail and not writing @playwright/test by default. It is suitable for E2E exploratory automation and UI process troubleshooting scenarios.
Read Moregh-fix-ci: Use GitHub CLI to let AI help you debug failed CI checks on PRs
If your CI fails before a PR is merged, do you have to switch back and forth between the Actions page and your terminal to check logs? The officially curated OpenAI skill `gh-fix-ci` is specifically designed for GitHub Actions failure troubleshooting: it pulls PR checks and run logs via the GitHub CLI, uses bundled scripts to automatically extract error snippets, provides a repair plan first, and waits for approval before you modify the code. This article introduces the positioning of this skill, the usage of `inspect_pr_checks.py`, as well as the installation and enabling methods in tools such as Codex and Cursor.
Read Moregh-address-comments: Structured Processing of GitHub PR Review Comments with Agent Skill
gh-address-comments is a curated Skill by OpenAI Codex. It pulls all review and inline comments of the current branch PR via gh CLI and GraphQL scripts, summarizes them with serial numbers for users to select the entries to handle, and then hands them over to the Agent for code modification. This article introduces its three-step workflow, the capabilities of fetch_comments.py, the installation methods of Codex and Cursor, as well as applicable scenarios and precautions under the human-in-the-loop design.
Read More# doc-coauthoring: Use a three-stage structured workflow to let Agents help you write clear technical specifications and decision documents
Doc-coauthoring is a documentation co-creation Skill in Anthropic's official Skills repository, targeting structured writing scenarios such as technical specifications, decision documents, RFCs, and PRDs. Instead of generating a full article at one time, it guides the Agent through three phases: context collection, section-by-section polishing, and reader testing. It first supplements background information through meta-questions and information dumping, then conducts brainstorming, screening, drafting and iterative revision by chapter, and finally uses a context-free Claude to simulate reader questions to identify blind spots in the document. This article introduces its core capabilities, installation methods in Cursor and Claude Code, as well as typical interaction examples and applicable boundaries for writing decision docs.
Read Moreinternal-comms: Let AI Write Internal Communication Documents According to Company Format
Anthropic's official Skill internal-comms packages internal communication templates such as 3P weekly reports, all-staff newsletters, FAQs, and incident reports into the SKILL.md instruction set. This article introduces its workflow for loading examples/ guidelines by category, the installation method in Cursor / Claude Code, as well as typical prompt usages and customization suggestions.
Read More# web-artifacts-builder: Using React Stack to Enable Agents to Deliver Deployable Frontend HTML Artifacts
Anthropic’s official Skill `web-artifacts-builder` builds complex multi-component web artifacts using React 18, TypeScript, Vite, Tailwind and shadcn/ui. The `init-artifact.sh` initializes the scaffold and pre-installs over 40 components, while `bundle-artifact.sh` packages the project into a self-contained `bundle.html`. This article covers the installation and activation methods for tools like Claude Code and Cursor, a four-step workflow, and applicable scenarios, helping AI Agents deliver web pages following modern front-end engineering practices.
Read MoreTheme Factory: One-click skin changing for slides, documents and landing pages with Agent Skill
### 翻译结果： This article introduces Anthropic's official theme-factory Skill: it includes 10 preset themes (color schemes and fonts), which can apply unified styles to slides, documents, reports and HTML landing pages, and also supports custom themes. Based on the official SKILL.md and repository structure, this article explains the installation methods (CLI, manual copying, Claude Code plugin), standard skin-changing process and typical prompt examples, which is suitable for developers who need to unify the style in AI design workflows.
Read MoreLet AI Truly Excel at Writing Excel: Detailed Explanation of Anthropic's Official xlsx Skill
xlsx is an official Anthropic Agent Skill dedicated to handling reading and writing of spreadsheet files such as .xlsx/.csv, formula modeling and data cleaning, and also serves as the implementation reference behind Claude's document capabilities. This article introduces its core capabilities (division of labor among openpyxl/pandas/markitdown, formula recalculation via recalc.py, and financial model specifications), as well as the installation, activation methods and typical usage scenarios in Cursor, Claude Code and Claude.ai, to help developers enable AI to directly deliver auditable spreadsheets.
Read MoreSkill for PPTX: Let AI Agents Truly Learn to Create PowerPoint Presentations
### 译文1（标准科技文档译法，适配海外技术社区表达）： > The official Anthropic PPTX Skill supports creation, editing and reading of `.pptx` and `.potx` files, with supporting scripts including `pptxgenjs`, OOXML decompression and editing utilities, and `validate.py`, as well as triple-layer QA. This article introduces its positioning, core capabilities, installation method in Cursor / Claude Code, typical usage scenarios and precautions for template filling, validation and visual QA. --- ### 译文2（更贴合海外开发者文档的口语化译法）： > Anthropic's official PPTX Skill lets you build, edit and read `.pptx` and `.potx` slides, backed by supporting tools like `pptxgenjs`, OOXML decompression/editing scripts, `validate.py`, plus a three-tier QA pipeline. We'll walk through its positioning, core features, how to install it in Cursor and Claude Code, plus common workflows for template population, validation and visual QA along with key best practices.
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