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moai-foundation-claudemoai foundation Claude 搜索

Agent Skill

moai-foundation-claude 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

1,616

周安装

66

GitHub Stars

964

下载量

523
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

3

许可证

MIT

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:moai-foundation-claude(moai foundation Claude 搜索)
来源仓库:https://github.com/modu-ai/moai-adk
仓库路径:skills/moai-foundation-claude
安装命令:
npx skills add https://github.com/modu-ai/moai-adk --skill moai-foundation-claude
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/modu-ai/moai-adk --skill moai-foundation-claude

简介

用于查找、检索和筛选相关信息,适合基于关键词定位内容。

  • 支持多轮交互和结果排序,便于 Agent 快速获取所需资料。
  • 通过 GitHub 安装,需确认是否触发联网或外部服务调用。
  • 权限和维护状态未明,建议在使用前测试小规模用例。
  • 适用于 Codex、Claude、Cursor 和 Gemini CLI,实际行为以仓库实现为准。

SKILL.md

Claude Code Authoring Kit

Comprehensive reference for Claude Code Skills, sub-agents, plugins, slash commands, hooks, memory, settings, sandboxing, headless mode, and advanced agent patterns.

Documentation Index

Core Features:

  • reference/claude-code-skills-official.md - Agent Skills creation and management
  • reference/claude-code-sub-agents-official.md - Sub-agent development and delegation
  • reference/claude-code-plugins-official.md - Plugin architecture and distribution
  • reference/claude-code-custom-slash-commands-official.md - Command creation and orchestration

Configuration:

  • reference/claude-code-settings-official.md - Configuration hierarchy and management
  • reference/claude-code-memory-official.md - Context and knowledge persistence
  • reference/claude-code-hooks-official.md - Event-driven automation
  • reference/claude-code-iam-official.md - Access control and security

Advanced Features:

  • reference/claude-code-sandboxing-official.md - Security isolation
  • reference/claude-code-headless-official.md - Programmatic and CI/CD usage
  • reference/claude-code-devcontainers-official.md - Containerized environments
  • reference/claude-code-cli-reference-official.md - Command-line interface
  • reference/claude-code-statusline-official.md - Custom status display
  • reference/advanced-agent-patterns.md - Engineering best practices

Quick Reference

Skills: Model-invoked extensions in ~/.claude/skills/ (personal) or.claude/skills/ (project). Three-level progressive disclosure. Max 500 lines.

Sub-agents: Specialized assistants via Agent(subagent_type="..."). Own 200K context. Cannot spawn sub-agents. Use /agents command.

Plugins: Reusable bundles in.claude-plugin/plugin.json. Include commands, agents, skills, hooks, MCP servers.

Commands: User-invoked via /command. Parameters: $ARGUMENTS, $1, $2. File refs: @file.

Hooks: Events in settings.json. PreToolUse, PostToolUse, SessionStart, SessionEnd, PreCompact, Notification.

Memory: CLAUDE.md files +.claude/rules/*.md. Enterprise to Project to User hierarchy. @import syntax.

Settings: 6-level hierarchy. Managed to file-managed to CLI to local to shared to user.

Sandboxing: OS-level isolation. Filesystem and network restrictions. Auto-allow safe operations.

Headless: -p flag for non-interactive. --allowedTools, --json-schema, --agents for automation.

Skill Creation

Progressive Disclosure Architecture

Level 1 (Metadata): Name and description loaded at startup, approximately 100 tokens per Skill

Level 2 (Instructions): SKILL.md body loaded when triggered, under 5K tokens recommended

Level 3 (Resources): Additional files loaded on demand, effectively unlimited

Required Format

Create a SKILL.md file with YAML frontmatter containing name in kebab-case and description explaining what it does and when to use it in third person. Maximum 1024 characters for description. After the frontmatter, include a heading with the skill name, a Quick Start section with brief instructions, and a Details section referencing REFERENCE.md for more information.

Best Practices

  • Third person descriptions (does not I do)
  • Include trigger terms users mention
  • Keep under 500 lines
  • One level deep references
  • Test with Haiku, Sonnet, Opus

Sub-agent Creation

Using /agents Command

Type /agents, select Create New Agent, define purpose and tools, press e to edit prompt.

File Format

Create a markdown file with YAML frontmatter containing name, description explaining when to invoke (use PROACTIVELY for auto-delegation), tools as comma-separated list (Read, Write, Bash), and model specification (sonnet). After frontmatter, include the system prompt.

Critical Rules

  • Cannot spawn other sub-agents
  • Cannot use AskUserQuestion effectively
  • All user interaction before delegation
  • Each gets own 200K context

Plugin Creation

Directory Structure

Create my-plugin directory with.claude-plugin/plugin.json, commands directory, agents directory, skills directory, hooks/hooks.json, and.mcp.json file.

Manifest (plugin.json)

Create a JSON object with name, description explaining plugin purpose, version as 1.0.0, and author object containing name field.

Commands

Use /plugin install owner/repo to install from GitHub. Use /plugin validate. to validate current directory. Use /plugin enable plugin-name to enable a plugin.

Advanced Agent Patterns

Two-Agent Pattern for Long Tasks

Initializer agent: Sets up environment, feature registry, progress docs

Executor agent: Works single features, updates registry, maintains progress

See reference/advanced-agent-patterns.md for details.

Orchestrator-Worker Architecture

Lead agent: Decomposes tasks, spawns workers, synthesizes results

Worker agents: Execute focused tasks, return condensed summaries

Context Engineering Principles

  • Smallest set of high-signal tokens
  • Just-in-time retrieval over upfront loading
  • Context compaction for long sessions
  • External memory files persist outside window

Tool Design Best Practices

  • Consolidate related functions into single tools
  • Return high-signal context-aware responses
  • Clear parameter names (user_id not user)
  • Instructive error messages with examples

Explore/Search Performance Optimization

When using Explore agent or direct exploration tools (Grep, Glob, Read), apply these optimizations to prevent performance bottlenecks with GLM models:

AST-Grep Priority

  • Use structural search (ast-grep) before text-based search (Grep)
  • Load moai-tool-ast-grep skill for complex pattern matching
  • Example: sg -p 'class $X extends Service' --lang python is faster than grep -r "class.*extends.*Service"

Search Scope Limitation

  • Always use path parameter to limit search scope
  • Example: Grep(pattern="func ", path="internal/core/") instead of Grep(pattern="async def")

File Pattern Specificity

  • Use specific Glob patterns instead of wildcards
  • Example: Glob(pattern="internal/core/*.go") instead of Glob(pattern="src/**/*.py")

Parallel Processing

  • Execute independent searches in parallel (single message, multiple tool calls)
  • Maximum 5 parallel searches to prevent context fragmentation

Workflow: Explore-Plan-Code-Commit

Phase 1 Explore: Read files, understand structure, map dependencies

Phase 2 Plan: Use think prompts, outline approach, define criteria

Phase 3 Code: Implement iteratively, verify each step, handle edges

Phase 4 Commit: Descriptive messages, logical groupings, clean history

MoAI-ADK Integration

Core Skills

  • moai-foundation-claude: This authoring kit
  • moai-foundation-core: SPEC system and workflows
  • moai-foundation-philosopher: Strategic thinking

Essential Sub-agents

  • spec-builder: EARS specifications
  • manager-ddd: DDD execution
  • expert-security: Security analysis
  • expert-backend: API development
  • expert-frontend: UI implementation

Security Features

Sandboxing

  • Filesystem: Write restricted to cwd
  • Network: Domain allowlists via proxy
  • OS-level: bubblewrap (Linux), Seatbelt (macOS)

Dev Containers

  • Security-hardened with firewall
  • Whitelisted outbound only
  • --dangerously-skip-permissions for trusted only

Headless Safety

  • Always use --allowedTools in CI/CD
  • Validate inputs before passing to Claude
  • Handle errors with exit codes

Resources

For detailed patterns and working examples, see the reference directory.

Version History:

  • v5.0.0 (2026-01-11): Converted to narrative format per CLAUDE.md Documentation Standards
  • v4.0.0 (2026-01-06): Added plugins, sandboxing, headless, statusline, dev containers, CLI reference, advanced patterns
  • v3.0.0 (2025-12-06): Added progressive disclosure, sub-agent details, integration patterns
  • v2.0.0 (2025-11-26): Initial comprehensive release

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

04

需要参考平台分布和安装热度时

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

补充不同宿主或平台的使用分布数据

能力 5

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

Claude Code

28.74%
按下载量换算150

OpenCode

21.77%
按下载量换算114

Gemini CLI

19.46%
按下载量换算102

Cursor

13.14%
按下载量换算69

Antigravity

8.39%
按下载量换算44

Codex

3.66%
按下载量换算19

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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/modu-ai/moai-adk --skill moai-foundation-claude;npx skills add modu-ai/moai-adk --skill "moai-foundation-claude" 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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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