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Configure Ecc

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xu-xiang
configure-ecc

Everything Claude Code 的交互式安装程序 — 引导用户选择并安装技能和规则到用户级或项目级目录,验证路径,并可选择优化已安装文件。

Overview

Publisherxu-xiang
Repositoryeverything-claude-code-zh
Skill nameconfigure-ecc
Stars
1.9K
Forks
318
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by xu-xiang on GitHub. Read the source before you install it.

Installation

Install the Configure Ecc AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/xu-xiang/everything-claude-code-zh.git /tmp/everything-claude-code-zh
mkdir -p .claude/skills
cp -r /tmp/everything-claude-code-zh/docs/zh-CN/skills/configure-ecc .claude/skills/configure-ecc
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Configure Ecc in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Configure Ecc on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Configure Ecc is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

配置 Everything Claude Code (ECC)

一个交互式、分步安装向导,用于 Everything Claude Code 项目。使用 AskUserQuestion 引导用户选择性安装技能和规则,然后验证正确性并提供优化。

何时激活

  • 用户说 "configure ecc"、"install ecc"、"setup everything claude code" 或类似表述
  • 用户想要从此项目中选择性安装技能或规则
  • 用户想要验证或修复现有的 ECC 安装
  • 用户想要为其项目优化已安装的技能或规则

先决条件

此技能必须在激活前对 Claude Code 可访问。有两种引导方式:

  1. 通过插件: /plugin install everything-claude-code — 插件会自动加载此技能
  2. 手动: 仅将此技能复制到 ~/.claude/skills/configure-ecc/SKILL.md,然后通过说 "configure ecc" 激活

步骤 0:克隆 ECC 仓库

在任何安装之前,将最新的 ECC 源代码克隆到 /tmp

bash
rm -rf /tmp/everything-claude-code
git clone https://github.com/affaan-m/everything-claude-code.git /tmp/everything-claude-code

ECC_ROOT=/tmp/everything-claude-code 设置为所有后续复制操作的源。

如果克隆失败(网络问题等),使用 AskUserQuestion 要求用户提供现有 ECC 克隆的本地路径。


步骤 1:选择安装级别

使用 AskUserQuestion 询问用户安装位置:

Question: "Where should ECC components be installed?"
Options:
  - "User-level (~/.claude/)" — "Applies to all your Claude Code projects"
  - "Project-level (.claude/)" — "Applies only to the current project"
  - "Both" — "Common/shared items user-level, project-specific items project-level"

将选择存储为 INSTALL_LEVEL。设置目标目录:

  • 用户级别:TARGET=~/.claude
  • 项目级别:TARGET=.claude(相对于当前项目根目录)
  • 两者:TARGET_USER=~/.claudeTARGET_PROJECT=.claude

如果目标目录不存在,则创建它们:

bash
mkdir -p $TARGET/skills $TARGET/rules

步骤 2:选择并安装技能

2a:选择技能类别

共有 27 项技能,分为 4 个类别。使用 AskUserQuestionmultiSelect: true

Question: "Which skill categories do you want to install?"
Options:
  - "Framework & Language" — "Django, Spring Boot, Go, Python, Java, Frontend, Backend patterns"
  - "Database" — "PostgreSQL, ClickHouse, JPA/Hibernate patterns"
  - "Workflow & Quality" — "TDD, verification, learning, security review, compaction"
  - "All skills" — "Install every available skill"

2b:确认单项技能

对于每个选定的类别,打印下面的完整技能列表,并要求用户确认或取消选择特定的技能。如果列表超过 4 项,将列表打印为文本,并使用 AskUserQuestion,提供一个 "安装所有列出项" 的选项,以及一个 "其他" 选项供用户粘贴特定名称。

类别:框架与语言(17 项技能)

技能描述
backend-patternsNode.js/Express/Next.js 的后端架构、API 设计、服务器端最佳实践
coding-standardsTypeScript、JavaScript、React、Node.js 的通用编码标准
django-patternsDjango 架构、使用 DRF 的 REST API、ORM、缓存、信号、中间件
django-securityDjango 安全性:身份验证、CSRF、SQL 注入、XSS 防护
django-tdd使用 pytest-django、factory_boy、模拟、覆盖率进行 Django 测试
django-verificationDjango 验证循环:迁移、代码检查、测试、安全扫描
frontend-patternsReact、Next.js、状态管理、性能、UI 模式
frontend-slides零依赖的 HTML 演示文稿、样式预览以及 PPTX 到网页的转换
golang-patterns地道的 Go 模式、构建健壮 Go 应用程序的约定
golang-testingGo 测试:表驱动测试、子测试、基准测试、模糊测试
java-coding-standardsSpring Boot 的 Java 编码标准:命名、不可变性、Optional、流
python-patternsPythonic 惯用法、PEP 8、类型提示、最佳实践
python-testing使用 pytest、TDD、固件、模拟、参数化进行 Python 测试
springboot-patternsSpring Boot 架构、REST API、分层服务、缓存、异步
springboot-securitySpring Security:身份验证/授权、验证、CSRF、密钥、速率限制
springboot-tdd使用 JUnit 5、Mockito、MockMvc、Testcontainers 进行 Spring Boot TDD
springboot-verificationSpring Boot 验证:构建、静态分析、测试、安全扫描

类别:数据库(3 项技能)

技能描述
clickhouse-ioClickHouse 模式、查询优化、分析、数据工程
jpa-patternsJPA/Hibernate 实体设计、关系、查询优化、事务
postgres-patternsPostgreSQL 查询优化、模式设计、索引、安全

类别:工作流与质量(8 项技能)

技能描述
continuous-learning从会话中自动提取可重用模式作为习得技能
continuous-learning-v2基于本能的学习,带有置信度评分,演变为技能/命令/代理
eval-harness用于评估驱动开发 (EDD) 的正式评估框架
iterative-retrieval用于子代理上下文问题的渐进式上下文优化
security-review安全检查清单:身份验证、输入、密钥、API、支付功能
strategic-compact在逻辑间隔处建议手动上下文压缩
tdd-workflow强制要求 TDD,覆盖率 80% 以上:单元测试、集成测试、端到端测试
verification-loop验证和质量循环模式

类别:业务与内容(5 项技能)

技能描述
article-writing使用笔记、示例或源文档,以指定的口吻进行长篇写作
content-engine多平台社交内容、脚本和内容再利用工作流
market-research带有来源标注的市场、竞争对手、基金和技术研究
investor-materials宣传文稿、一页简介、投资者备忘录和财务模型
investor-outreach个性化的投资者冷邮件、熟人介绍和后续跟进

独立技能

技能描述
project-guidelines-example用于创建项目特定技能的模板

2c:执行安装

对于每个选定的技能,复制整个技能目录:

bash
cp -r $ECC_ROOT/skills/<skill-name> $TARGET/skills/

注意:continuous-learningcontinuous-learning-v2 有额外的文件(config.json、钩子、脚本)——确保复制整个目录,而不仅仅是 SKILL.md。


步骤 3:选择并安装规则

使用 AskUserQuestionmultiSelect: true

Question: "Which rule sets do you want to install?"
Options:
  - "Common rules (Recommended)" — "Language-agnostic principles: coding style, git workflow, testing, security, etc. (8 files)"
  - "TypeScript/JavaScript" — "TS/JS patterns, hooks, testing with Playwright (5 files)"
  - "Python" — "Python patterns, pytest, black/ruff formatting (5 files)"
  - "Go" — "Go patterns, table-driven tests, gofmt/staticcheck (5 files)"

执行安装:

bash
# Common rules (flat copy into rules/)
cp -r $ECC_ROOT/rules/common/* $TARGET/rules/

# Language-specific rules (flat copy into rules/)
cp -r $ECC_ROOT/rules/typescript/* $TARGET/rules/   # if selected
cp -r $ECC_ROOT/rules/python/* $TARGET/rules/        # if selected
cp -r $ECC_ROOT/rules/golang/* $TARGET/rules/        # if selected

重要:如果用户选择了任何特定语言的规则但没有选择通用规则,警告他们:

"特定语言规则扩展了通用规则。不安装通用规则可能导致覆盖不完整。是否也安装通用规则?"


步骤 4:安装后验证

安装后,执行这些自动化检查:

4a:验证文件存在

列出所有已安装的文件并确认它们存在于目标位置:

bash
ls -la $TARGET/skills/
ls -la $TARGET/rules/

4b:检查路径引用

扫描所有已安装的 .md 文件中的路径引用:

bash
grep -rn "~/.claude/" $TARGET/skills/ $TARGET/rules/
grep -rn "../common/" $TARGET/rules/
grep -rn "skills/" $TARGET/skills/

对于项目级别安装,标记任何对 ~/.claude/ 路径的引用:

  • 如果技能引用 ~/.claude/settings.json — 这通常没问题(设置始终是用户级别的)
  • 如果技能引用 ~/.claude/skills/~/.claude/rules/ — 如果仅安装在项目级别,这可能损坏
  • 如果技能通过名称引用另一项技能 — 检查被引用的技能是否也已安装

4c:检查技能间的交叉引用

有些技能会引用其他技能。验证这些依赖关系:

  • django-tdd 可能引用 django-patterns
  • springboot-tdd 可能引用 springboot-patterns
  • continuous-learning-v2 引用 ~/.claude/homunculus/ 目录
  • python-testing 可能引用 python-patterns
  • golang-testing 可能引用 golang-patterns
  • 特定语言规则引用其 common/ 对应项

4d:报告问题

对于发现的每个问题,报告:

  1. 文件:包含问题引用的文件
  2. 行号:行号
  3. 问题:哪里出错了(例如,"引用了 ~/.claude/skills/python-patterns 但 python-patterns 未安装")
  4. 建议的修复:该怎么做(例如,"安装 python-patterns 技能" 或 "将路径更新为 .claude/skills/")

步骤 5:优化已安装文件(可选)

使用 AskUserQuestion

Question: "Would you like to optimize the installed files for your project?"
Options:
  - "Optimize skills" — "Remove irrelevant sections, adjust paths, tailor to your tech stack"
  - "Optimize rules" — "Adjust coverage targets, add project-specific patterns, customize tool configs"
  - "Optimize both" — "Full optimization of all installed files"
  - "Skip" — "Keep everything as-is"

如果优化技能:

  1. 读取每个已安装的 SKILL.md
  2. 询问用户其项目的技术栈是什么(如果尚不清楚)
  3. 对于每项技能,建议删除无关部分
  4. 在安装目标处就地编辑 SKILL.md 文件(不是源仓库)
  5. 修复在步骤 4 中发现的任何路径问题

如果优化规则:

  1. 读取每个已安装的规则 .md 文件
  2. 询问用户的偏好:
    • 测试覆盖率目标(默认 80%)
    • 首选的格式化工具
    • Git 工作流约定
    • 安全要求
  3. 在安装目标处就地编辑规则文件

关键:只修改安装目标($TARGET/)中的文件,绝不修改源 ECC 仓库($ECC_ROOT/)中的文件。


步骤 6:安装摘要

/tmp 清理克隆的仓库:

bash
rm -rf /tmp/everything-claude-code

然后打印摘要报告:

## ECC Installation Complete

### Installation Target
- Level: [user-level / project-level / both]
- Path: [target path]

### Skills Installed ([count])
- skill-1, skill-2, skill-3, ...

### Rules Installed ([count])
- common (8 files)
- typescript (5 files)
- ...

### Verification Results
- [count] issues found, [count] fixed
- [list any remaining issues]

### Optimizations Applied
- [list changes made, or "None"]

故障排除

"Claude Code 未获取技能"

  • 验证技能目录包含一个 SKILL.md 文件(不仅仅是松散的 .md 文件)
  • 对于用户级别:检查 ~/.claude/skills/<skill-name>/SKILL.md 是否存在
  • 对于项目级别:检查 .claude/skills/<skill-name>/SKILL.md 是否存在

"规则不工作"

  • 规则是平面文件,不在子目录中:$TARGET/rules/coding-style.md(正确)对比 $TARGET/rules/common/coding-style.md(对于平面安装不正确)
  • 安装规则后重启 Claude Code

"项目级别安装后出现路径引用错误"

  • 有些技能假设 ~/.claude/ 路径。运行步骤 4 验证来查找并修复这些问题。
  • 对于 continuous-learning-v2~/.claude/homunculus/ 目录始终是用户级别的 — 这是预期的,不是错误。

Frequently asked questions

What does the Configure Ecc AI skill do?

Everything Claude Code 的交互式安装程序 — 引导用户选择并安装技能和规则到用户级或项目级目录,验证路径,并可选择优化已安装文件。

Why use Configure Ecc on TypingMind?

Because you install it once and use it with any model. Configure Ecc is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Configure Ecc in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/xu-xiang/everything-claude-code-zh/tree/main/docs/zh-CN/skills/configure-ecc. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Configure Ecc?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Configure Ecc?

As many as you like. As long as a model supports skills, you can use Configure Ecc with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Configure Ecc AI skill free?

Yes. It is published on GitHub by xu-xiang under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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