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Agent Skill · 前端设计

reflect(技能安全扫描)

用于辅助前端页面、组件、样式和交互逻辑的开发与维护。它适合让 Agent 生成或审查 React、Next.js、Vue、Tailwind、CSS 等相关代码,整理组件结构,或定位布局和性能问题。使用时需要结合项目现有设计系统、路由和构建方式,避免只生成孤立片段;涉及页面改动时,应配合本地预览和构建检查确认视觉效果。

reflect 是前端设计类 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;许可证为 MIT,第三方扫描已通过,按安装量在前端设计类的 10,216 个 Skill 里排第 5,455。

总安装 667周安装 27GitHub Stars 127下载 210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
MIT

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:reflect(技能安全扫描)
来源仓库:https://github.com/anton-abyzov/specweave
仓库路径:skills/reflect
安装命令:
npx skills add https://github.com/anton-abyzov/specweave --skill reflect
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/anton-abyzov/specweave --skill reflect

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

Reflect 可以一次正确,到处应用: 在会议期间进行更正 反映捕捉和技能路线 未来的会话从 CLAUDE.md 加载 克劳德自动应用学到的模式 没有嵌入。没有矢量数据库。只是您的 CLAUDE.md 文件,其中包含有组织的学习内容。

针对特定项目的学习 在开始工作之前,检查特定于项目的学习内容: # 检查该技能的技能记忆是否存在 cat .specweave/skill-memories/reflect.md 2 > /dev/null || echo "还没有项目学习" 当开发过程中发现更正或模式时,反思系统会自动捕获项目经验。

这些知识可以帮助您了解特定于项目的惯例和过去的决策。每周安装量 27 号 存储库 安东阿比佐夫 GitHub 之星 127 第一次看到 2026 年 1 月 22 日 安全审计 Gen Agent Trust Hub 通行证

来源仓库内路径:skills/reflect

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/anton-abyzov/specweave --skill reflect;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

reflect 怎么安装?

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

reflect 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。

reflect 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。

reflect 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

reflect 用的人多吗?

公开数据是累计安装 667 次,近一周安装 27 次,下载 210 次,GitHub 127 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。

reflect 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 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

  • 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。
  • 需要处理前端设计类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
reflect

技能安全扫描 · 本页

667127操作浏览器MIT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

Self-Improving Skills (Reflect)

Overview

The Reflect system enables continual learning across sessions. Instead of starting from zero every conversation, Claude learns from corrections, successful patterns, and user preferences - persisting knowledge in CLAUDE.md's Skill Memories section.

Session 1: User corrects workflow → Reflect captures learning → saves to CLAUDE.md
Session 2: Claude uses correct approach without being reminded
Session 3+: Knowledge compounds, Claude gets smarter over time

Architecture

Single Source of Truth: CLAUDE.md

All learnings are stored in your project's CLAUDE.md file under the ## Skill Memories section:

## Skill Memories

<!-- Auto-captured by SpecWeave reflect. Edit or delete as needed. -->

### Devops
- **2026-01-29**: LSP requires ENABLE_LSP_TOOL=1 env var + boostvolt/claude-code-lsps marketplace

### Frontend
- **2026-01-28**: Use shadcn/ui Button component, not custom styles
- **2026-01-27**: Prefer Vercel over Cloudflare for this Remix project

### General
- **2026-01-29**: Always check for credentials FIRST before using CLI tools

Why CLAUDE.md?

  • Single file to manage (no scattered MEMORY.md files)
  • Version controlled with your project
  • Easy to edit, review, or delete learnings
  • Automatically loaded by Claude Code

What It Learns

✅ DOES Remember

CategoryExamples
Skill-specific preferences"frontend: Use shadcn/ui Button component"
Workflow preferences"general: User prefers /sw:auto to run tests first"
Project conventions"devops: Use pnpm instead of npm for this monorepo"
Tool configurations"testing: Run Vitest with --pool=forks for this project"

❌ Does NOT Remember

CategoryWhy Not
Generic coding advice"use TypeScript strict mode" - not SpecWeave-specific
One-time fixesWon't recur, clutters memory
Implementation detailsUnrelated to SpecWeave workflow

⚠️ CRITICAL: Learning Extraction Rules

This section is MANDATORY for Claude to follow when extracting learnings.

The Golden Rule

NEVER store user input verbatim. ALWAYS synthesize into actionable rules.

What Makes a Good Learning

Good LearningBad LearningWhy Bad
Use vi.fn() for mocks in Vitest, never jest.fn()use vi.fn()Too terse, missing context
Always specify npm registry to avoid auth errorsAlways specify registry to avoid ~/Truncated, loses meaning
Voice dictation mangles slash commands - type manuallyalways command not recognizedRaw symptom, not the learning

Learning Quality Checklist (MUST PASS ALL)

Before storing ANY learning, verify:

  1. ✅ Is it a complete sentence? Not truncated, not a fragment
  2. ✅ Is it actionable? Contains DO/DON'T/USE/AVOID/PREFER
  3. ✅ Is it specific? Names tools, patterns, files, or concepts
  4. ✅ Is it understandable standalone? Someone reading it later would understand
  5. ✅ Is it NOT a question? Questions are never learnings
  6. ✅ Does it have context? WHY this rule exists, not just WHAT

What to REJECT (Never Store)

  1. Questions - "Where should I deploy?" → NOT a learning
  2. Fragments - "eplicilty how to g" → Truncated garbage
  3. Raw symptoms - "always command not recognized" → No explanation
  4. Duplicates - Same rule phrased differently
  5. Temporary context - "for this PR", "just this time"
  6. Typos/gibberish - "user pojrect", "promp"

Skill Categories

Learnings are routed to these known skills:

SkillWhat it covers
mobileReact Native, Expo, iOS, Android
frontendReact, Vue, Next.js, UI components
backendAPIs, Node.js,.NET, databases
testingVitest, Jest, Playwright, E2E
infrastructureTerraform, AWS, Azure, GCP
kubernetesK8s, EKS, AKS, GKE, Helm
architectSystem design, ADRs, patterns
tech-leadCode review, best practices
qa-leadTest strategy, quality gates
securityAuth, OWASP, vulnerabilities
docs-writerDocumentation, READMEs
performanceOptimization, profiling
tdd-orchestratorTDD workflow, red-green-refactor
pmProduct management, specs
devopsCI/CD, Docker, deployments
paymentsStripe, payment processing
mlMachine learning, AI
githubGitHub sync, issues, PRs
jiraJIRA sync, tickets
adoAzure DevOps sync
generalFallback for general SpecWeave learnings

Usage

Manual Reflection

After completing work, manually trigger reflection:

# Reflect on current session (auto-detects skills)
/sw:reflect

# Reflect with focus prompt
/sw:reflect "Focus on the deployment patterns we discussed"

Automatic Reflection

Enable auto-reflection on session end:

# Enable automatic reflection (via stop hook)
/sw:reflect-on

# Disable automatic reflection
/sw:reflect-off

# Check reflection status
/sw:reflect-status

When enabled, the stop hook automatically:

  1. Analyzes the session transcript
  2. Extracts SpecWeave-specific learnings via LLM
  3. Routes to appropriate skill category
  4. Updates CLAUDE.md Skill Memories section

Configuration

In .specweave/config.json:

{
  "reflect": {
    "enabled": true,
    "model": "haiku",
    "maxLearningsPerSession": 3
  }
}
SettingDefaultDescription
enabledtrueMaster switch for reflection
model"haiku"LLM model for extraction
maxLearningsPerSession3Limit per session

Disable reflection: Set "reflect": {"enabled": false}


How It Works

Extraction Flow

1. Session ends or /sw:reflect invoked
        ↓
2. Session transcript captured
        ↓
3. LLM analyzes for SpecWeave learnings
        ↓
4. Learnings validated (quality gates)
        ↓
5. Deduplicated against existing memory
        ↓
6. Written to CLAUDE.md Skill Memories

LLM Extraction

Uses Claude Haiku (fast, cheap) to extract learnings:

interface SkillLearning {
  skill: string;    // e.g., "frontend", "devops", "general"
  learning: string; // The actual learning content
}

Deduplication

Learnings are considered duplicates if:

  • Content has >50% substring overlap with existing
  • Same skill and semantically identical

Best Practices

For Corrections (High Signal)

Good corrections (will be captured):

"Never use that approach. Always use X because..."
"Don't create custom components. We have a design system..."
"Wrong pattern. The correct way is..."

Weak corrections (may be ignored):

"Hmm, maybe try something else?"
"That doesn't look quite right"

For Approvals (Medium Signal)

Strong approval (will be captured):

"Perfect! That's exactly how we do it."
"This is the right pattern, well done."

Neutral (won't be captured):

"OK"
"Sure"
"Proceed"

Managing Learnings

View Current Learnings

Check your CLAUDE.md file's ## Skill Memories section.

Edit Learnings

Simply edit CLAUDE.md directly. Add, modify, or delete any entry.

Clear Learnings

# Clear all learnings
/sw:reflect-clear

# Clear specific skill
/sw:reflect-clear --skill frontend

Status Check

/sw:reflect-status

Shows:

  • Whether reflection is enabled
  • Recent learnings
  • Learning counts per skill

Troubleshooting

Learnings Not Persisting

  1. Check reflection is enabled: /sw:reflect-status
  2. Verify CLAUDE.md exists in project root
  3. Check config: cat.specweave/config.json | grep reflect
  4. Review logs: ls.specweave/logs/reflect/

Wrong Skill Detection

The LLM routes learnings based on content. If misrouted:

  • Edit CLAUDE.md directly to move the learning
  • Use specific language: "For frontend development..."

Garbage Learnings

If you see truncated or nonsensical entries:

  1. Delete them from CLAUDE.md
  2. They were likely from voice dictation or partial input

Privacy & Security

  • Memory contains only patterns and learnings, not raw conversation
  • No sensitive data (credentials, keys) is ever stored
  • CLAUDE.md is in your repo - gitignore if needed
  • Clear commands available to remove learnings

Integration with Auto Mode

When /sw:auto runs with reflection enabled:

1. Start auto session
        ↓
2. Claude executes tasks
        ↓
3. Session completes
        ↓
4. Stop hook triggers
        ↓
5. Reflect analyzes transcript
        ↓
6. CLAUDE.md updated
        ↓
7. Session ends with summary

Summary

Reflect enables correct once, apply everywhere:

  1. Make correction during session
  2. Reflect captures and routes to skill
  3. Future sessions load from CLAUDE.md
  4. Claude applies learned patterns automatically

No embeddings. No vector databases. Just your CLAUDE.md file with organized learnings.

Project-Specific Learnings

Before starting work, check for project-specific learnings:

# Check if skill memory exists for this skill
cat .specweave/skill-memories/reflect.md 2>/dev/null || echo "No project learnings yet"

Project learnings are automatically captured by the reflection system when corrections or patterns are identified during development. These learnings help you understand project-specific conventions and past decisions.

平台分布

Claude Code

29.43%
按下载量换算62

Antigravity

23.53%
按下载量换算49

Gemini CLI

20.81%
按下载量换算44

OpenCode

12.24%
按下载量换算26

Cursor

9.45%
按下载量换算20

Codex

3.49%
按下载量换算7

安全审计

Gen Agent Trust Hub

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。

继续浏览同类 Skills