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creating-claude-agents

Use when creating or improving Claude Code agents. Expert guidance on agent file structure, frontmatter, persona definition, tool access, model selection, and validation against schema.

DeepseekModel キュレーション済みスキル 品質 優秀 · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=agentworkforce-relay-claude-skills-creating-claude-agents-skill-skill-md&format=skill
ダウンロード .skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
name creating-claude-agents description Use when creating or improving Claude Code agents. Expert guidance on agent file structure, frontmatter, persona definition, tool access, model selection, and validation against schema. Creating Claude Code Agents - Expert Skill Use this skill when creating or improving Claude Code agents. Provides comprehensive guidance on agent structure, schema validation, and best practices for building long-running AI assistants. When to Use This Skill Activate this skill when: User asks to create a new Claude Code agent User wants to improve an existing agent User needs help with agent frontmatter or structure User is troubleshooting agent validation issues User wants to understand agent format requirements User asks about agent vs skill vs slash command differences Quick Reference Agent File Structure --- name: agent-name description: When and why to use this agent allowed-tools: Read, Write, Bash model: sonnet agentType: agent --- # 🔍 Agent Display Name You are [persona definition - describe the agent's role and expertise]. ## Instructions [Clear, actionable guidance on what the agent does] ## Process [Step-by-step workflow the agent follows] ## Examples [Code samples and use cases demonstrating the agent's capabilities] File Location Required Path: .claude/agents/*.md Agents must be placed in .claude/agents/ directory as markdown files. Frontmatter Requirements Required Fields Field Type Description Example name string Agent identifier (lowercase, hyphens only) code-reviewer description string Brief overview of functionality and use cases Reviews code for best practices and potential issues Optional Fields Field Type Description Values allowed-tools string Comma-separated list of available tools Read, Write, Bash, WebSearch model string Claude model to use sonnet , opus , haiku , inherit agentType string Explicit marker for format preservation agent Validation Rules Name Field: Pattern: ^[a-z0-9-]+$ (lowercase letters, numbers, hyphens only) Max length: 64 characters Example: ✅ code-reviewer ❌ Code_Reviewer Description Field: Max length: 1024 characters Should clearly explain when to use the agent Start with action words: "Reviews...", "Analyzes...", "Helps with..." Allowed Tools: Valid tools: Read , Write , Edit , Grep , Glob , Bash , WebSearch , WebFetch , Task , Skill , SlashCommand , TodoWrite , AskUserQuestion Model Values: sonnet - Balanced, good for most agents (default) opus - Complex reasoning, architectural decisions haiku - Fast, simple tasks inherit - Use parent conversation's model Content Format Requirements H1 Heading (Required) The first line of content must be an H1 heading that serves as the agent's display title: # 🔍 Code Reviewer Best Practices: Include an emoji icon for visual distinction Use title case Keep concise (2-5 words) Make it descriptive and memorable Persona Definition (Required for Agents) Immediately after the H1, define the agent's persona using "You are..." format: You are an expert code reviewer with deep knowledge of software engineering principles and security best practices. Guidelines: Start with "You are..." Define role and expertise clearly Set expectations for the agent's capabilities Establish the agent's approach and tone Content Structure # 🔍 Agent Name You are [persona definition]. ## Instructions [What the agent does and how it approaches tasks] ## Process 1. [Step 1] 2. [Step 2] 3. [Step 3] ## Examples [Code samples showing good/bad patterns] ## Guidelines - [Best practice 1] - [Best practice 2] Schema Validation Agents must conform to the JSON schema at: https://github.com/pr-pm/prpm/blob/main/packages/converters/schemas/claude-agent.schema.json Schema Structure { "frontmatter" : { "name" : "string (required)" , "description" : "string (required)" , "allowed-tools" : "string (optional)" , "model" : "enum (optional)" , "agentType" : "agent (optional)" } , "content" : "string (markdown with H1, persona, instructions)" } Common Validation Errors Error Cause Fix Missing required field 'name' Frontmatter lacks name field Add name: agent-name Missing required field 'description' Frontmatter lacks description Add description: ... Invalid name pattern Name contains uppercase or special chars Use lowercase and hyphens only Name too long Name exceeds 64 characters Shorten the name Invalid model value Model not in enum Use: sonnet , opus , haiku , or inherit Missing H1 heading Content doesn't start with # Add # Agent Name as first line Tool Configuration Inheriting All Tools Omit the allowed-tools field to inherit all tools from the parent conversation: --- name: full-access-agent description: Agent needs access to everything # No allowed-tools field = inherits all --- Specific Tools Only Grant minimal necessary permissions: --- name: read-only-reviewer description: Reviews code without making changes allowed-tools: Read, Grep, Bash --- Bash Tool Restrictions Use command patterns to restrict Bash access: --- name: git-helper description: Git operations only allowed-tools: Bash(git *), Read --- Syntax: Bash(git *) - Only git commands Bash(npm test:*) - Only npm test scripts Bash(git status:*) , Bash(git diff:*) - Multiple specific commands Model Selection Guide Sonnet (Most Agents) Use for: Code review Debugging Data analysis General problem-solving model: sonnet Opus (Complex Reasoning) Use for: Architecture decisions Complex refactoring Deep security analysis Novel problem-solving model: opus Haiku (Speed Matters) Use for: Syntax checks Simple formatting Quick validations Low-latency needs model: haiku Inherit (Context-Dependent) Use for: Agent should match user's model choice Cost sensitivity model: inherit Common Mistakes Mistake Problem Solution Using _ in name Violates pattern constraint Use hyphens: code-reviewer not code_reviewer Uppercase in name Violates pattern constraint Lowercase only: debugger not Debugger Missing persona Agent lacks role definition Add "You are..." after H1 No H1 heading Content format invalid Start content with # Agent Name Vague description Agent won't activate correctly Be specific about when to use Too many tools Security risk, violates least privilege Grant only necessary tools No agentType field May lose type info in conversion Add agentType: agent Generic agent name Conflicts or unclear purpose Use specific, descriptive names Best Practices 1. Write Clear, Specific Descriptions The description determines when Claude automatically invokes your agent. ✅ Good: description: Reviews code changes for quality, security, and maintainability issues ❌ Poor: description: A helpful agent # Too vague 2. Define Strong Personas Establish expertise and approach immediately after the H1: # 🔍 Code Reviewer You are an expert code reviewer specializing in TypeScript and React, with 10+ years of experience in security-focused development. You approach code review systematically, checking for security vulnerabilities, performance issues, and maintainability concerns. 3. Provide Step-by-Step Processes Guide the agent's workflow explicitly: ## Review Process 1. **Read the changes** - Get recent git diff or specified files - Understand the context and purpose 2. **Analyze systematically** - Check each category (quality, security, performance) - Provide specific file:line references - Explain why something is an issue 3. **Provide actionable feedback** - Categorize by severity - Include fix suggestions - Highlight positive patterns 4. Include Examples Show both good and bad patterns: ## Examples When reviewing error handling: ❌ **Bad - Silent failure:** \ `\` \`typescript try { await fetchData(); } catch (error) { console.log(error); } \ `\` \` ✅ **Good - Proper error handling:** \ `\` \`typescript try { await fetchData(); } catch (error) { logger.error('Failed to fetch data', error); throw new AppError('Data fetch failed', { cause: error }); } \ `\` \` 5. Use Icons in H1 for Visual Distinction Choose emojis that represent the agent's purpose: 🔍 Code Reviewer 🐛 Debugger 📊 Data Scientist 🔒 Security Auditor ⚡ Performance Optimizer 📝 Documentation Writer 🧪 Test Generator 6. Maintain Single Responsibility Each agent should excel at ONE specific task: ✅ Good: code-reviewer - Reviews code for quality and security debugger - Root cause analysis and minimal fixes ❌ Poor: code-helper - Reviews, debugs, tests, refactors, documents (too broad) 7. Grant Minimal Tool Access Follow the principle of least privilege: # Read-only analysis agent allowed-tools: Read, Grep # Code modification agent allowed-tools: Read, Edit, Bash(git *) # Full development agent allowed-tools: Read, Write, Edit, Bash, Grep, Glob 8. Include agentType for Round-Trip Conversion Always include agentType: agent in frontmatter to preserve type information during format conversions: --- name: code-reviewer description: Reviews code for best practices agentType: agent ---
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ダウンロードした .skill に含まれるフィールド。
フィールド 説明
formatフォーマット識別子(skill/v1)
skill_idスキル固有 ID
nameスキル名
versionバージョン
description説明
categoryカテゴリ(配列)
trigger_wordsトリガーワード
tagsタグ
sourceソース
source_urlソース URL(本ページ)
exported_atエクスポート日時(ダウンロード毎)
system_promptシステムプロンプト本文
model_configモデル設定:provider / model / temperature / max_tokens / top_p
examplesサンプル
install_guide各プラットフォームの導入説明(Coze / Dify / Claude / カスタム)
同じスキルを各プラットフォーム形式で出力できます。
.skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能 ダウンロード
.skillpro 拡張形式。scripts / tools / dependencies / hooks を含む ダウンロード
.json 純粋な JSON 出力。system_prompt とモデル設定のみ ダウンロード
Coze frontmatter 付き Markdown。Coze へのインポート用 ダウンロード
Dify Dify DSL。アプリ作成後にそのままインポート ダウンロード

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