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init初始化

Agent Skill

init 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

2,448

周安装

102

GitHub Stars

163

下载量

816
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:init(初始化)
来源仓库:https://github.com/flora131/atomic
仓库路径:skills/init
安装命令:
npx skills add https://github.com/flora131/atomic --skill init
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/flora131/atomic --skill init

简介

init 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据任务场景定位候选结果。
  • 通过 npx skills add 命令从指定仓库安装并使用。
  • 需确认权限范围和维护状态,注意是否触发联网或文件读写。
  • init 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Generate CLAUDE.md and AGENTS.md

You are tasked with exploring the current codebase with the codebase-analyzer, codebase-locator, codebase-pattern-finder sub-agents, detecting the primary project languages, checking whether the corresponding language servers already exist on the user's machine, optionally installing any missing language servers after explicit user confirmation, and then generating populated CLAUDE.md and AGENTS.md files at the project root. These files provide coding agents with the context they need to work effectively in this repository.

Steps

  1. Explore the codebase to discover project metadata:

- Read package.json, Cargo.toml, go.mod, pyproject.toml, Gemfile, pom.xml, or similar manifest files - Scan the top-level directory structure (src/, lib/, app/, tests/, docs/, etc.) - Check for existing config files: .eslintrc, tsconfig.json, biome.json, oxlint.json, .prettierrc, CI configs (.github/workflows/, .gitlab-ci.yml), etc. - Read README.md if it exists for project description and setup instructions - Check for .env.example, .env.local, or similar environment files - Identify the package manager (bun, npm, yarn, pnpm, cargo, go, pip, etc.) - Identify the primary project languages from manifests, lockfiles, and source file extensions - Inspect editor/tooling config such as .vscode, language-specific config files, or existing LSP settings when present

  1. Identify key project attributes:

- Project name: From manifest file or directory name - Project purpose: 1-2 sentence description from README or manifest - Project structure: Key directories and their purposes - Tech stack: Language, framework, runtime - Detected languages: The main implementation languages in the repo - Recommended LSPs: The language servers that best match those languages - Commands: dev, build, test, lint, typecheck, format (from scripts in manifest) - Environment setup: Required env vars, env example files - Verification command: The command to run before commits (usually lint + typecheck + test) - Existing documentation: Links to docs within the repo

  1. Detect installed language servers and prepare an installation plan:

- For each detected language, choose the most standard LSP for that ecosystem and prefer already configured tooling when the repo clearly indicates a preference - Check whether each LSP is already available by using non-destructive discovery commands such as command -v, --version, or equivalent read-only checks - Use this default mapping unless the repo clearly points to a different choice: - TypeScript / JavaScript -> typescript-language-server (and ensure typescript is available when required) - Python -> pyright - Go -> gopls - Rust -> rust-analyzer - Ruby -> ruby-lsp - PHP -> intelephense - Lua -> lua-language-server - Bash / shell -> bash-language-server - YAML -> yaml-language-server - Docker -> dockerfile-language-server-nodejs - Terraform -> terraform-ls - Java -> jdtls - Kotlin -> kotlin-language-server - C / C++ -> clangd - C# -> csharp-ls - If an LSP is missing, prepare the safest install command that fits the user's available tooling and platform; do not guess a package manager that is not installed - If the required runtime or package manager is missing, stop short of installation and report what is needed instead

  1. Ask for confirmation before installing anything:

- Summarize the detected languages, the LSPs already present, the LSPs that are missing, and the exact install commands you plan to run - Ask the user for confirmation before running any install command - If the user declines, skip installation and continue with documentation generation - After installation, verify each newly installed LSP with a version check or binary lookup and mention any failures clearly

  1. Populate the template below with discovered values. Replace every {{placeholder}} with actual values from the repo. Delete sections that don't apply (e.g., Environment if there are no env files). Remove the "How to Fill This Template" meta-section entirely.
  2. Write the populated content to both CLAUDE.md and AGENTS.md at the project root with identical content.

Template

# {{PROJECT_NAME}}

## Overview

{{1-2 sentences describing the project purpose}}

## Project Structure

| Path         | Type     | Purpose     |
| ------------ | -------- | ----------- |
| \`{{path}}\` | {{type}} | {{purpose}} |

## Quick Reference

### Languages and Tooling

- Languages: {{comma-separated detected languages}}
- LSPs: {{comma-separated installed or recommended language servers}}

### Commands

\`\`\`bash
{{dev_command}} # Start dev server / all services
{{build_command}} # Build the project
{{test_command}} # Run tests
{{lint_command}} # Lint & format check
{{typecheck_command}} # Type-check (if applicable)
\`\`\`

### Environment

- Copy \`{{env_example_file}}\` → \`{{env_local_file}}\` for local development
- Required vars: {{comma-separated list of required env vars}}

## Progressive Disclosure

Read relevant docs before starting:
| Topic | Location |
| ----- | -------- |
| {{topic}} | \`{{path_to_doc}}\` |

## Universal Rules

1. Run \`{{verify_command}}\` before commits
2. Keep PRs focused on a single concern
3. {{Add any project-specific universal rules}}

## Code Quality

Formatting and linting are handled by automated tools:

- \`{{lint_command}}\` — {{linter/formatter names}}
- \`{{format_command}}\` — Auto-fix formatting (if separate from lint)

Run before committing. Don't manually check style—let tools do it.

Important Notes

  • Keep it under 100 lines (ideally under 60) after populating
  • Every instruction must be universally applicable to all tasks in the repo
  • No code style rules — delegate to linters/formatters
  • No task-specific instructions — use the progressive disclosure table
  • No code snippets — use file:line pointers instead
  • Include verification commands the agent can run to validate work
  • Never install tooling without an explicit user confirmation first
  • Prefer read-only discovery before installation and verify any installed LSP afterward
  • Delete any section from the template that doesn't apply to this project
  • Do NOT include the "How to Fill This Template" section in the output
  • Write identical content to both CLAUDE.md and AGENTS.md at the project root

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

36.15%
按下载量换算295

Claude

29.61%
按下载量换算242

Cursor

19.34%
按下载量换算158

Gemini CLI

9.37%
按下载量换算76

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/flora131/atomic --skill init 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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