Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
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This skill should be used when the user asks to "create a plugin", "scaffold a plugin", "understand plugin structure", "organize plugin components", "set up plugin.json", "use ${CLAUDE_PLUGIN_ROOT}", "add commands/agents/skills/hooks", "configure auto-discovery", or needs guidance on plugin directory layout, manifest configuration, component organization, file naming conventions, or Claude Code plugin architecture best practices.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Claude Code plugins follow a standardized directory structure with automatic component discovery. Understanding this structure enables creating well-organized, maintainable plugins that integrate seamlessly with Claude Code.
Key concepts:
.claude-plugin/plugin.json${CLAUDE_PLUGIN_ROOT}Every Claude Code plugin follows this organizational pattern:
plugin-name/
├── .claude-plugin/
│ └── plugin.json # Required: Plugin manifest
├── commands/ # Slash commands (.md files)
├── agents/ # Subagent definitions (.md files)
├── skills/ # Agent skills (subdirectories)
│ └── skill-name/
│ └── SKILL.md # Required for each skill
├── hooks/
│ └── hooks.json # Event handler configuration
├── .mcp.json # MCP server definitions
└── scripts/ # Helper scripts and utilities
Critical rules:
plugin.json manifest MUST be in .claude-plugin/ directory.claude-plugin/The manifest defines plugin metadata and configuration. Located at .claude-plugin/plugin.json:
{
"name": "plugin-name"
}
Name requirements:
code-review-assistant, test-runner, api-docs{
"name": "plugin-name",
"version": "1.0.0",
"description": "Brief explanation of plugin purpose",
"author": {
"name": "Author Name",
"email": "author@example.com",
"url": "https://example.com"
},
"homepage": "https://docs.example.com",
"repository": "https://github.com/user/plugin-name",
"license": "MIT",
"keywords": ["testing", "automation", "ci-cd"]
}
Version format: Follow semantic versioning (MAJOR.MINOR.PATCH) Keywords: Use for plugin discovery and categorization
Specify custom paths for components (supplements default directories):
{
"name": "plugin-name",
"commands": "./custom-commands",
"agents": ["./agents", "./specialized-agents"],
"hooks": "./config/hooks.json",
"mcpServers": "./.mcp.json"
}
Important: Custom paths supplement defaults—they don't replace them. Components in both default directories and custom paths will load.
Path rules:
./Location: commands/ directory
Format: Markdown files with YAML frontmatter
Auto-discovery: All .md files in commands/ load automatically
Example structure:
commands/
├── review.md # /review command
├── test.md # /test command
└── deploy.md # /deploy command
File format:
---
name: command-name
description: Command description
---
Command implementation instructions...
Usage: Commands integrate as native slash commands in Claude Code
Location: agents/ directory
Format: Markdown files with YAML frontmatter
Auto-discovery: All .md files in agents/ load automatically
Example structure:
agents/
├── code-reviewer.md
├── test-generator.md
└── refactorer.md
File format:
---
description: Agent role and expertise
capabilities:
- Specific task 1
- Specific task 2
---
Detailed agent instructions and knowledge...
Usage: Users can invoke agents manually, or Claude Code selects them automatically based on task context
Location: skills/ directory with subdirectories per skill
Format: Each skill in its own directory with SKILL.md file
Auto-discovery: All SKILL.md files in skill subdirectories load automatically
Example structure:
skills/
├── api-testing/
│ ├── SKILL.md
│ ├── scripts/
│ │ └── test-runner.py
│ └── references/
│ └── api-spec.md
└── database-migrations/
├── SKILL.md
└── examples/
└── migration-template.sql
SKILL.md format:
---
name: Skill Name
description: When to use this skill
version: 1.0.0
---
Skill instructions and guidance...
Supporting files: Skills can include scripts, references, examples, or assets in subdirectories
Usage: Claude Code autonomously activates skills based on task context matching the description
Location: hooks/hooks.json or inline in plugin.json
Format: JSON configuration defining event handlers
Registration: Hooks register automatically when plugin enables
Example structure:
hooks/
├── hooks.json # Hook configuration
└── scripts/
├── validate.sh # Hook script
└── check-style.sh # Hook script
Configuration format:
{
"PreToolUse": [{
"matcher": "Write|Edit",
"hooks": [{
"type": "command",
"command": "bash ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/validate.sh",
"timeout": 30
}]
}]
}
Available events: PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification
Usage: Hooks execute automatically in response to Claude Code events
Location: .mcp.json at plugin root or inline in plugin.json
Format: JSON configuration for MCP server definitions
Auto-start: Servers start automatically when plugin enables
Example format:
{
"mcpServers": {
"server-name": {
"command": "node",
"args": ["${CLAUDE_PLUGIN_ROOT}/servers/server.js"],
"env": {
"API_KEY": "${API_KEY}"
}
}
}
}
Usage: MCP servers integrate seamlessly with Claude Code's tool system
Use ${CLAUDE_PLUGIN_ROOT} environment variable for all intra-plugin path references:
{
"command": "bash ${CLAUDE_PLUGIN_ROOT}/scripts/run.sh"
}
Why it matters: Plugins install in different locations depending on:
Where to use it:
Never use:
/Users/name/plugins/...)./scripts/... in commands)~/plugins/...)In manifest JSON fields (hooks, MCP servers):
"command": "${CLAUDE_PLUGIN_ROOT}/scripts/tool.sh"
In component files (commands, agents, skills):
Reference scripts at: ${CLAUDE_PLUGIN_ROOT}/scripts/helper.py
In executed scripts:
#!/bin/bash
# ${CLAUDE_PLUGIN_ROOT} available as environment variable
source "${CLAUDE_PLUGIN_ROOT}/lib/common.sh"
Commands: Use kebab-case .md files
code-review.md → /code-reviewrun-tests.md → /run-testsapi-docs.md → /api-docsAgents: Use kebab-case .md files describing role
test-generator.mdcode-reviewer.mdperformance-analyzer.mdSkills: Use kebab-case directory names
api-testing/database-migrations/error-handling/Scripts: Use descriptive kebab-case names with appropriate extensions
validate-input.shgenerate-report.pyprocess-data.jsDocumentation: Use kebab-case markdown files
api-reference.mdmigration-guide.mdbest-practices.mdConfiguration: Use standard names
hooks.json.mcp.jsonplugin.jsonClaude Code automatically discovers and loads components:
.claude-plugin/plugin.json when plugin enablescommands/ directory for .md filesagents/ directory for .md filesskills/ for subdirectories containing SKILL.mdhooks/hooks.json or manifest.mcp.json or manifestDiscovery timing:
Override behavior: Custom paths in plugin.json supplement (not replace) default directories
Logical grouping: Group related components together
scripts/ for different purposesMinimal manifest: Keep plugin.json lean
Documentation: Include README files
Consistency: Use consistent naming across components
test-runner, name related agent test-runner-agentClarity: Use descriptive names that indicate purpose
api-integration-testing/, code-quality-checker.mdutils/, misc.md, temp.shLength: Balance brevity with clarity
review-pr, run-ci)code-reviewer, test-generator)error-handling, api-design)Single command with no dependencies:
my-plugin/
├── .claude-plugin/
│ └── plugin.json # Just name field
└── commands/
└── hello.md # Single command
Complete plugin with all component types:
my-plugin/
├── .claude-plugin/
│ └── plugin.json
├── commands/ # User-facing commands
├── agents/ # Specialized subagents
├── skills/ # Auto-activating skills
├── hooks/ # Event handlers
│ ├── hooks.json
│ └── scripts/
├── .mcp.json # External integrations
└── scripts/ # Shared utilities
Plugin providing only skills:
my-plugin/
├── .claude-plugin/
│ └── plugin.json
└── skills/
├── skill-one/
│ └── SKILL.md
└── skill-two/
└── SKILL.md
Component not loading:
SKILL.md (not README.md or other name)Path resolution errors:
${CLAUDE_PLUGIN_ROOT}./ in manifestecho $CLAUDE_PLUGIN_ROOT in hook scriptsAuto-discovery not working:
.claude-plugin/)Conflicts between plugins:
For detailed examples and advanced patterns, see files in references/ and examples/ directories.
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Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.