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Use when creating or configuring Claude Code agents and their frontmatter.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/Galaxy-Dawn/claude-scholar --skill agent-identifierコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
SKILL.md を表示中
Use this by default for non-trivial multi-step work that needs persistent planning, progress tracking, or durable notes on disk. Trigger when a task will likely span multiple tool calls, research steps, verification loops, or enough context that the plan should not live only in transient chat memory.
Polish, restructure, or translate academic prose into Nature-leaning English using writing-strategy principles, curated Nature/Nature Communications article patterns, and phrase-level support from Academic Phrasebank. Use whenever the user asks to polish a manuscript paragraph, abstract, introduction, results, discussion, conclusion, title, methods section, or Chinese academic draft for publication-quality English.
Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Use when the user wants to write or rebuild an abstract, introduction, results narrative, discussion, conclusion, title, or full manuscript argument rather than only polish finished prose.
SOC 職業分類に基づく
| name | agent-identifier |
| description | Use when creating or configuring Claude Code agents and their frontmatter. |
| version | 0.1.0 |
Agents are autonomous subprocesses that handle complex, multi-step tasks independently. Understanding agent structure, triggering conditions, and system prompt design enables creating powerful autonomous capabilities.
Key concepts:
Use this skill when the user asks to:
Do not use this skill for:
plugin-structure---
name: agent-identifier
description: Use this agent when [triggering conditions]. Examples:
<>
Context: [Situation description]
user: "[User request]"
assistant: "[How assistant should respond and use this agent]"
[Why this agent should be triggered]
[Additional example...]
model: inherit
color: blue
You are [agent role description]...
[Responsibility 1]
[Responsibility 2]
[Step-by-step workflow]
[What to return]
Agent identifier used for namespacing and invocation.
Format: lowercase, numbers, hyphens only Length: 3-50 characters Pattern: Must start and end with alphanumeric
Good examples:
code-reviewertest-generatorapi-docs-writersecurity-analyzerBad examples:
helper (too generic)-agent- (starts/ends with hyphen)my_agent (underscores not allowed)ag (too short, < 3 chars)Defines when Claude should trigger this agent. This is the most critical field.
Must include:
<example> blocks showing usage<commentary> explaining why agent triggersFormat:
Use this agent when [conditions]. Examples:
<example>
Context: [Scenario description]
user: "[What user says]"
assistant: "[How Claude should respond]"
<commentary>
[Why this agent is appropriate]
</commentary>
</example>
[More examples...]
Best practices:
Which model the agent should use.
Options:
inherit - Use same model as parent (recommended)sonnet - Claude Sonnet (balanced)opus - Claude Opus (most capable, expensive)haiku - Claude Haiku (fast, cheap)Recommendation: Use inherit unless agent needs specific model capabilities.
Visual identifier for agent in UI.
Options: blue, cyan, green, yellow, magenta, red
Guidelines:
Restrict agent to specific tools.
Format: Array of tool names
tools: ["Read", "Write", "Grep", "Bash"]
Default: If omitted, agent has access to all tools
Best practice: Limit tools to minimum needed (principle of least privilege)
Common tool sets:
["Read", "Grep", "Glob"]["Read", "Write", "Grep"]["Read", "Bash", "Grep"]["*"]The markdown body becomes the agent's system prompt. Write in second person, addressing the agent directly.
Standard template:
You are [role] specializing in [domain].
**Your Core Responsibilities:**
1. [Primary responsibility]
2. [Secondary responsibility]
3. [Additional responsibilities...]
**Analysis Process:**
1. [Step one]
2. [Step two]
3. [Step three]
[...]
**Quality Standards:**
- [Standard 1]
- [Standard 2]
**Output Format:**
Provide results in this format:
- [What to include]
- [How to structure]
**Edge Cases:**
Handle these situations:
- [Edge case 1]: [How to handle]
- [Edge case 2]: [How to handle]
✅ DO:
❌ DON'T:
Use this prompt pattern (extracted from Claude Code):
Create an agent configuration based on this request: "[YOUR DESCRIPTION]"
Requirements:
1. Extract core intent and responsibilities
2. Design expert persona for the domain
3. Create comprehensive system prompt with:
- Clear behavioral boundaries
- Specific methodologies
- Edge case handling
- Output format
4. Create identifier (lowercase, hyphens, 3-50 chars)
5. Write description with triggering conditions
6. Include 2-3 <example> blocks showing when to use
Return JSON with:
{
"identifier": "agent-name",
"whenToUse": "Use this agent when... Examples: <example>...</example>",
"systemPrompt": "You are..."
}
Then convert to agent file format with frontmatter.
See examples/agent-creation-prompt.md for complete template.
inherit)agents/agent-name.md✅ Valid: code-reviewer, test-gen, api-analyzer-v2
❌ Invalid: ag (too short), -start (starts with hyphen), my_agent (underscore)
Rules:
Length: 10-5,000 characters Must include: Triggering conditions and examples Best: 200-1,000 characters with 2-4 examples
Length: 20-10,000 characters Best: 500-3,000 characters Structure: Clear responsibilities, process, output format
plugin-name/
└── agents/
├── analyzer.md
├── reviewer.md
└── generator.md
All .md files in agents/ are auto-discovered.
Agents are namespaced automatically:
agent-nameplugin:subdir:agent-nameCreate test scenarios to verify agent triggers correctly:
Ensure system prompt is complete:
---
name: simple-agent
description: Use this agent when... Examples: <example>...</example>
model: inherit
color: blue
---
You are an agent that [does X].
Process:
1. [Step 1]
2. [Step 2]
Output: [What to provide]
| Field | Required | Format | Example |
|---|---|---|---|
| name | Yes | lowercase-hyphens | code-reviewer |
| description | Yes | Text + examples | Use when... ... |
| model | Yes | inherit/sonnet/opus/haiku | inherit |
| color | Yes | Color name | blue |
| tools | No | Array of tool names | ["Read", "Grep"] |
DO:
inherit for model unless specific needDON'T:
For detailed guidance, consult:
references/system-prompt-design.md - Complete system prompt patternsreferences/triggering-examples.md - Example formats and best practicesreferences/agent-creation-system-prompt.md - The exact prompt from Claude CodeWorking examples in examples/:
agent-creation-prompt.md - AI-assisted agent generation templatecomplete-agent-examples.md - Full agent examples for different use casesDevelopment tools in scripts/:
validate-agent.sh - Validate agent file structuretest-agent-trigger.sh - Test if agent triggers correctlyTo create an agent for a plugin:
agents/agent-name.md filescripts/validate-agent.shFocus on clear triggering conditions and comprehensive system prompts for autonomous operation.