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Agent Skill · 研究检索

build(构建)

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。

build 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 47,825。

总安装 717周安装 29GitHub Stars 167下载 225核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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-superpowers
仓库路径:skills/build
安装命令:
npx skills add https://github.com/whawkinsiv/claude-code-superpowers --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-superpowers --skill build

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

build 用于查找、检索和筛选相关信息。适用于构建流程中的信息支持与资源匹配。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。支持在 Codex、Claude、Cursor、Gemini CLI 中使用。

安装前需确认其是否具备执行构建命令或访问依赖库的权限。build 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/build

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/whawkinsiv/claude-code-superpowers --skill bui…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

build 怎么安装?

在终端执行 npx skills add https://github.com/whawkinsiv/claude-code-superpowers --skill build。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

build 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

build 需要什么权限?

权限级别是操作浏览器。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。

build 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

build 用的人多吗?

公开数据是累计安装 717 次,近一周安装 29 次,下载 225 次,GitHub 167 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

build 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
build

构建 · 本页

717167操作浏览器未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

平台分布

Codex

34.26%
按下载量换算77

Claude

33.5%
按下载量换算75

Cursor

18.9%
按下载量换算43

Gemini CLI

10.38%
按下载量换算23

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。目前只有一个公开来源,建议同时核对源仓库。

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