github-trending

majiayu000/claude-arsenal · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/majiayu000/claude-arsenal --skill github-trending
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summary

Real-time discovery and analysis of GitHub trending repositories, developers, and technology trends.

  • Tracks trending projects across languages, timeframes (daily/weekly/monthly), and categories; identifies viral, steady-growth, and niche projects worth monitoring
  • Analyzes projects using metrics like star velocity, contributor activity, documentation quality, and community responsiveness to distinguish hype from genuine value
  • Covers emerging tech domains including AI/LLM tooling, Rust
skill.md

GitHub Trending 探索

核心能力

  • 趋势发现 — 实时获取 GitHub Trending 仓库和开发者
  • 技术洞察 — 分析热门项目背后的技术栈和架构
  • 社区脉搏 — 理解开发者社区的兴趣偏好和需求
  • 机会识别 — 发现潜在的开源贡献机会和学习方向

使用场景

场景 命令示例
探索今日热门 "看看今天 GitHub 上什么项目火了"
语言趋势 "Rust 最近有什么热门项目"
领域研究 "AI/ML 领域最近的趋势项目"
竞品分析 "看看有没有类似 X 的热门项目"
技术选型 "有什么热门的 React 组件库"
学习方向 "最近什么技术在快速增长"

数据源

Primary: GitHub Trending

https://github.com/trending                    # 总榜
https://github.com/trending/{language}         # 按语言
https://github.com/trending?since=daily        # 今日
https://github.com/trending?since=weekly       # 本周
https://github.com/trending?since=monthly      # 本月
https://github.com/trending/developers         # 热门开发者

Secondary: GitHub API

# 搜索高星项目
https://api.github.com/search/repositories?q=stars:>1000+pushed:>2024-01-01&sort=stars

# 最近创建的热门项目
https://api.github.com/search/repositories?q=created:>2024-06-01+stars:>100&sort=stars

Supplementary Sources


分析框架

项目评估维度

## 基础指标
- Stars / Star 增长速度
- Forks / Fork 活跃度
- Contributors 数量
- Issue/PR 活跃度
- 最近提交频率

## 质量指标
- README 完整度
- 文档质量
- 测试覆盖率
- CI/CD 配置
- License 类型

## 社区指标
- Issue 响应时间
- PR 合并效率
- Discussions 活跃度
- 社区友好度 (good first issue)

## 趋势指标
- Star 增长曲线 (线性/指数/爆发)
- 媒体曝光度
- 被 fork/依赖的情况
- 相关生态项目

趋势解读模板

## 项目名称: {name}

### 一句话总结
{这个项目解决什么问题,为什么火}

### 核心数据
- Stars: X (本周 +Y)
- Language: Z
- Created: YYYY-MM-DD
- License: MIT/Apache/etc

### 为什么火
1. {原因1: 解决了什么痛点}
2. {原因2: 技术上有何创新}
3. {原因3: 社区/营销做得好}

### 技术亮点
- {亮点1}
- {亮点2}

### 适用场景
- {场景1}
- {场景2}

### 潜在风险/局限
- {风险1}
- {风险2}

### 相关/竞品项目
- {项目A}: 区别是...
- {项目B}: 区别是...

趋势分类

按热度类型

## 1. 爆发型 (Viral)
- 特征: 短时间内 star 暴涨 (1天1000+)
- 原因: HN/Reddit 首页、名人推荐、解决热点问题
- 风险: 可能只是 hype,需观察持续性

## 2. 稳定增长型 (Steady)
- 特征: 持续稳定增长 (每天 10-100 stars)
- 原因: 真正解决问题,口碑传播
- 信号: 通常质量较高,值得关注

## 3. 周期型 (Cyclical)
- 特征: 随特定事件周期性上榜
- 例如: 年度总结类项目、面试题库
- 特点: 可预测,有特定时间窗口

## 4. 长尾型 (Long Tail)
- 特征: 低调但持续有用
- 原因: 特定领域的刚需工具
- 价值: 往往是真正的生产力工具

按项目类型

## 工具类
- CLI 工具
- 开发者效率工具
- 系统工具

## 框架类
- Web 框架
- UI 组件库
- 测试框架

## AI/ML 类
- LLM 应用
- AI 工具链
- 模型相关

## 学习资源类
- Awesome 列表
- 教程/指南
- 面试准备

## 基础设施类
- 数据库
- 消息队列
- 监控运维

深度分析技巧

识别真正有价值的项目

## 真正有价值的项目通常具备:
✓ 解决明确的痛点问题
✓ 有清晰的使用场景
✓ 代码质量高,架构合理
✓ 文档完善,易于上手
✓ 维护活跃,响应及时
✓ 社区友好,欢迎贡献

## 可能只是 Hype 的信号:
✗ 只有 README,代码很少
✗ 概念大于实现
✗ Star 多但 Fork 少
✗ Issue 积压严重
✗ 只有一个维护者
✗ 没有实际使用案例

预测潜力项目

## 早期信号
- 知名开发者/公司背书
- 解决新兴技术的痛点
- 独特的技术方案
- 清晰的 Roadmap
- 活跃的早期社区

## 增长潜力判断
1. 市场: 目标用户群体大小
2. 竞争: 是否有强力竞品
3. 技术: 是否有护城河
4. 团队: 维护者背景和投入
5. 生态: 是否容易集成

技术趋势追踪

2024-2025 热点领域

## AI/LLM 工具链
- RAG 框架 (LangChain, LlamaIndex)
- Agent 框架 (AutoGPT, CrewAI)
- 本地 LLM (Ollama, llama.cpp)
- AI Code Assistant

## Rust 生态爆发
- 系统工具 Rust 重写
- Web 框架 (Axum, Actix)
- 前端工具链 (SWC, Turbopack)

## Developer Experience
- AI 辅助开发
- 开发环境容器化
- 类型安全全栈

## 边缘计算
- Edge Runtime (Cloudflare Workers, Deno Deploy)
- WASM 应用

## 可观测性
- OpenTelemetry 生态
- eBPF 工具

语言趋势

## 上升趋势
- Rust: 系统编程、WebAssembly
- Go: 云原生、CLI 工具
- TypeScript: 全栈开发、类型安全
- Zig: 系统编程新秀

## 稳定主流
- Python: AI/ML、脚本
- JavaScript: Web 开发
- Java/Kotlin: 企业后端

## 特定领域
- Swift: Apple 生态
- C#: 游戏、Windows
- Elixir: 高并发系统

输出格式

趋势日报

# GitHub Trending 日报 - {date}

## 今日亮点
{简短总结今日最值得关注的趋势}

## 热门项目 TOP 5

### 1. {project_name} ⭐ {stars} (+{daily_increase})
> {one_line_description}

**语言**: {language} | **License**: {license}
**为什么火**: {reason}
**适合谁**: {target_audience}

[GitHub]({url}) | [Demo]({demo_url})

---

### 2. ...

## 技术趋势观察
- {trend_observation_1}
- {trend_observation_2}

## 值得关注的新项目
{刚起步但有潜力的项目}

## 本周回顾
{如果是周末,加入周总结}

领域深度报告

# {领域} 技术趋势报告

## 概述
{领域现状和趋势概述}

## 主流方案对比

| 项目 | Stars | 特点 | 适用场景 |
|------|-------|------|----------|
| A    | 10k   | ...  | ...      |
| B    | 8k    | ...  | ...      |

## 技术演进
{技术发展脉络}

## 选型建议
{根据不同需求的推荐}

## 未来展望
{预测未来发展方向}

实践建议

如何利用 Trending

## 学习
- 阅读热门项目源码
how to use github-trending

How to use github-trending on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add github-trending
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/majiayu000/claude-arsenal --skill github-trending

The skills CLI fetches github-trending from GitHub repository majiayu000/claude-arsenal and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/github-trending

Reload or restart Cursor to activate github-trending. Access the skill through slash commands (e.g., /github-trending) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.665 reviews
  • Chaitanya Patil· Dec 28, 2024

    Keeps context tight: github-trending is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Noor Singh· Dec 24, 2024

    Solid pick for teams standardizing on skills: github-trending is focused, and the summary matches what you get after install.

  • Diego Nasser· Dec 20, 2024

    github-trending is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Zaid Gonzalez· Dec 12, 2024

    github-trending has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Amelia Abebe· Nov 23, 2024

    github-trending fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Piyush G· Nov 19, 2024

    github-trending has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Camila Gill· Nov 19, 2024

    We added github-trending from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Xiao Liu· Nov 15, 2024

    github-trending is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Neel Huang· Nov 11, 2024

    Solid pick for teams standardizing on skills: github-trending is focused, and the summary matches what you get after install.

  • Sofia Jain· Nov 3, 2024

    Keeps context tight: github-trending is the kind of skill you can hand to a new teammate without a long onboarding doc.

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