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ワンクリックでManusで任意のスキルを実行
始める$pwd:
$ git log --oneline --stat
stars:1,194
forks:98
updated:2026年5月26日 09:56
ファイルエクスプローラー
SKILL.md
28 ファイル
readonly
$ install --global
$ download --local
$ useful --forSOC
Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
智能对话分析与记忆整理助手。获取并压缩指定 Agent 的对话记录，用于在用户授权/触发条件满足时，将信息分类写入 USER.md / AGENT.md / MEMORY.md（含索引与 memory/ 日志）/ IDENTITY.md / SOUL.md。
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
Use this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions "deck," "slides," "presentation," or references a .pptx filename, regardless of what they plan to do with the content afterward. If a .pptx file needs to be opened, created, or touched, use this skill.
| name | deep-research-agent |
| description | 深度研究技能，用于系统性调研与分析。适用于研究、调研、竞品分析、市场分析或结构化信息收集等需求。 |
以增量方式开展系统化研究并输出。
1. 大纲 → 2. 初始化 → 3. 研究 → 4. 更新 → 5. JSON → 6. HTML
研究前先向用户展示大纲：
获得用户确认后再继续。
运行初始化脚本，使用绝对路径创建工作目录：
python skills/deep-research-agent/scripts/init_research.py <absolute_template_path> <absolute_project_path>
用法： python init_research.py <absolute_template_path> <absolute_project_path>
模板（研究方向模板）：
不同研究类型使用对应的 Markdown 模板：
模板统一放在 deep-research-agent/templates 目录下，初始化时只需选择对应模板文件路径。
创建内容：
report.md - 复制选定模板（位于项目目录）materials/ - 原始资料与笔记目录（包含 raw/ 与 notes/）重要： 不要用 mkdir 或 Write tool 手动创建目录，必须通过初始化脚本生成结构。
搜索并立即保存：
每条有价值的信息都要 先保存到 materials 目录：
file_write(
file_path="{project_path}/materials/raw/source_001.md",
content="""## 来源: [标题]
- URL: [链接]
- 时间: [日期]
### 关键信息
- [要点1]
- [要点2]
### 数据
- [数据点]
### 引用原文
> [原文摘录]
"""
)
研究策略：
materials/当某一节内容充足时，立即更新报告：
file_update(
file_path="{project_path}/report.md",
operations=[{
"update_mode": "search_replace",
"search_pattern": "## 1. 研究背景与目标\n\n{研究背景说明}",
"replacement": """## 1. 研究背景与目标
### 1.1 研究背景
[基于materials/中的资料，撰写详细背景]
[包含数据支撑、引用来源]
### 1.2 研究目标
[具体目标]
### 1.3 研究范围
[范围界定]"""
}]
)
更新规则：
[在此填写...]、{占位符} 等）在生成最终输出前，必须执行以下检查：
report.md 中是否还有未填充的模板占位符（如 {研究背景说明}、{在此填写...}、[请填写...] 等）检查通过后，生成包含结构化数据的 research_data.json：
{
"topic": "...",
"created_at": "...",
"outline": {...},
"materials_count": 15,
"sections_completed": ["1.1", "1.2", "3.1"],
"key_findings": [...],
"sources": [...]
}
{user_specified_project_path}/
├── report.md # 主报告（增量更新）
├── report.html # 阅读友好的 HTML 版本
├── research_data.json # 结构化数据
└── materials/
├── raw/ # 原始来源
├── notes/ # 按章节整理的笔记
└── ...
materials/research_data.json 与报告保持一致scripts/md_to_html.py 生成。
python skills/deep-research-agent/scripts/md_to_html.py /absolute/path/report.md--out 指定输出路径。模板位置：deep-research-agent/templates。无需在此列出具体模板名称。