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build构建

Agent Skill

build 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

269

周安装

11

GitHub Stars

168

下载量

86
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:build(构建)
来源仓库:https://github.com/whawkinsiv/claude-code-skills
仓库路径:skills/build
安装命令:
npx skills add https://github.com/whawkinsiv/claude-code-skills --skill build
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/whawkinsiv/claude-code-skills --skill build

简介

build 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词快速定位候选结果。
  • 通过 npx skills add 命令从指定仓库安装并使用。
  • 安装前需确认权限范围、维护状态,避免触发联网或命令执行。
  • 建议结合原始 README 核验具体用法和功能边界。

SKILL.md

Build

Tool Selection

Starting from scratch? → Lovable (fastest MVP) Existing codebase? → Claude Code (best context) Learning to code? → Replit (educational) Already code? → Cursor (power features)

See TOOLS.md for detailed comparison.


Build Workflow

- [ ] Start with spec (use scope skill)
- [ ] Give spec to AI tool
- [ ] Test happy path + edge cases
- [ ] Give specific feedback on issues
- [ ] Iterate (expect 2-4 rounds)
- [ ] Deploy when working

Giving AI Your Spec

Claude Code

Build this feature: [paste spec]

Codebase: React + TypeScript + Tailwind
Reference: src/components/Button.tsx for button patterns

Lovable

Build: [paste simplified spec focusing on outcome]
Make it look like Linear (minimal, clean)

Replit

Create: [paste spec emphasizing what user sees]
Use React. Keep simple.

See PROMPTS.md for patterns.


Build in Pieces, Not All at Once

The biggest mistake non-technical founders make: giving AI the entire spec and hoping it comes back perfect. It won't. AI tools work best in focused chunks.

The Build Loop:

1. Pick ONE piece (a single feature or flow)
2. Give AI a clear spec for just that piece
3. Test it — does the piece work?
4. Fix any issues before moving on
5. Pick the next piece → repeat

Good pieces (1-3 hours each):

  • User signup and login
  • Dashboard showing key metrics
  • Settings page with profile editing
  • One core workflow (e.g., "create an invoice")

Bad pieces (too big):

  • "Build the whole app"
  • "Build the dashboard with all integrations"
  • "User management with roles, permissions, and team features"

Quality Gate Between Pieces

Before building the next feature, check: Does the previous feature still work? Can you sign up, do the core action, and see the result? AI tools sometimes break existing features while adding new ones. Catch that early.

When to Start a Fresh Session

Start a new chat/session with your AI tool when:

  • AI has made 3+ attempts at the same fix without success — context is polluted
  • You're seeing new bugs appear every time a bug is fixed
  • The AI is going in circles (suggesting things it already tried)
  • You want to add a new feature after finishing the current one

When starting fresh, give AI a clear description of: what exists, what works, and what you need next. Don't assume it remembers.

Things AI Won't Add Unless You Ask

AI-built projects routinely ship without these. Add them explicitly:

Ask Your AI Tool to Add:
- [ ] Error tracking (Sentry) — so you know when things break
- [ ] Analytics snippet (Plausible, PostHog, or GA4) — so you know who visits
- [ ] Proper 404 page — so broken links don't show a blank screen
- [ ] Proper 500 page — so server errors show a helpful message
- [ ] Favicon — so your browser tab has an icon, not a blank square
- [ ] Meta tags (title, description, OG image) — so links look good when shared
- [ ] Loading states — so users know something is happening

Reviewing What AI Built

Test, don't just run:

- [ ] Looks right?
- [ ] Happy path works?
- [ ] Edge cases work?
- [ ] Works on mobile?
- [ ] Error messages clear?

Giving Feedback

Bad: "This doesn't work" Good: "Clicking 'Save' does nothing. Expected: 'Saved!' message"

Template:

What I tried: [action]
Expected: [outcome]
Got: [what happened]

Iteration Expectations

Normal: 2-4 rounds per feature First build: AI builds from spec, you find 3-5 issues Second build: Fixes those, you find 1-2 more Third build: Final polish

Stop when:

  • Happy path works
  • Edge cases handled
  • Mobile works
  • No obvious bugs

Don't iterate for:

  • Perfection
  • Features beyond spec
  • Premature optimization

Common Mistakes

MistakeFix
No specUse scope skill first
"Build a dashboard"Specify what's on it
Skip edge case testingTry breaking it
Accept without reviewAlways test
Add features mid-buildFinish current feature first
Fix code yourselfDescribe problem, let AI fix

Right-Sizing Work

Too big: "Build entire app" Too small: "Add one button" Right: "Build user auth flow" (1-3 hours)

Good chunks:

  • User login/signup flow
  • Dashboard with 4 metrics
  • Settings page with profile editing

When Stuck

AI keeps breaking things: → Break into smaller piece, start fresh session

Can't figure out complex feature: → Ask: "What's simplest way?" Accept simpler solution

Each fix breaks something else: → Stop. Ask: "Better approach?" Consider starting over


Working with Existing Code

Add [feature] to existing project.

Stack: [React, Next.js, etc]
Patterns: Check src/components for examples
Style: Tailwind + custom design system
Follow existing code style

Prompting Patterns

Reference existing:

Build Settings page.
Reference Dashboard page layout.
Use same Card/Button components.

Provide examples:

Pricing page with 3 tiers.
Like Linear's pricing - clean, minimal.

Specify constraints:

Build profile page.
Must work offline.
Load under 2 seconds.
WCAG AA accessible.

See PROMPTS.md for more.


Review for Non-Technical Founders

Check:

  • Does it match spec?
  • Buttons work?
  • Forms validate?
  • Looks like design reference?
  • Works on mobile?
  • Error messages clear?

Don't check:

  • Code cleanliness
  • Optimization
  • "Best practices"

AI handles code quality. You handle requirements.


Success Looks Like

✅ Features match specs ✅ 2-4 iterations (not 10+) ✅ Can explain what's wrong ✅ Building faster each week

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.6%
按下载量换算30

Claude

32.87%
按下载量换算28

Cursor

17.74%
按下载量换算15

Gemini CLI

9.55%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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