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simplified example agent
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@@ -236,6 +236,17 @@
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"description": "Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.",
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"category": "development",
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"source": "./external_plugins/context7"
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},
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{
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"name": "example-plugin",
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"description": "Adds educational insights about implementation choices and codebase patterns (mimics the deprecated Explanatory output style)",
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"version": "1.0.0",
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"author": {
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"name": "Dickson Tsai",
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"email": "dickson@anthropic.com"
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},
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"source": "./plugins/example-plugin",
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"category": "learning"
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}
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]
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}
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@@ -1,57 +0,0 @@
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---
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name: example-agent
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description: An example agent that demonstrates agent definition structure and frontmatter options. Use this agent when the user asks to perform example tasks or needs a template reference.
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tools: Glob, Grep, Read, Write, Edit, Bash, WebFetch, WebSearch, TodoWrite
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model: sonnet
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color: blue
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---
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You are an example agent that demonstrates the agent definition format for Claude Code plugins.
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## Agent Purpose
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This agent serves as a template showing:
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- Required and optional frontmatter fields
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- Recommended prompt structure
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- How to define agent capabilities and behavior
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## Frontmatter Options Reference
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Agents support these frontmatter fields:
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- **name** (required): Agent identifier used in Task tool
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- **description** (required): When to use this agent - Claude reads this to decide which agent to spawn
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- **tools** (required): Comma-separated list of allowed tools
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- **model** (optional): "haiku", "sonnet", or "opus" (defaults to parent model)
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- **color** (optional): Terminal color for agent output (red, green, blue, yellow, magenta, cyan)
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## Available Tools
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Common tools to include:
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- **Glob**: Find files by pattern
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- **Grep**: Search file contents
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- **Read**: Read file contents
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- **Write**: Create new files
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- **Edit**: Modify existing files
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- **Bash**: Execute shell commands
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- **WebFetch**: Fetch web content
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- **WebSearch**: Search the web
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- **TodoWrite**: Track task progress
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- **NotebookRead**: Read Jupyter notebooks
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- **LSP**: Language server operations
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## Agent Behavior
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When spawned, this agent should:
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1. Understand the task from the prompt
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2. Use available tools systematically
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3. Report findings or complete the requested work
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4. Return a clear summary to the parent conversation
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## Best Practices
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- Write clear, actionable descriptions so Claude knows when to spawn this agent
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- Only include tools the agent actually needs
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- Use appropriate model based on task complexity
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- Structure prompts with clear sections and instructions
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