據 AlphaMoat 統計,截至 2026-09,xmind 累計下載 2,491 次、獲 0 個星標,在全部 5,078 個 AI 技能中排名第 4,102 位,在「知識管理」分類(442 個)中排名第 354 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 43 | 1449 | - | - |
| SkillHub ↗ | 347 | 2491 | - | — |
各平台的計數口徑不同,統計時間不一致。
使用 mcporter、npx 和固定版本的 xmind-generator-mcp,將提綱整理為主題並生成 .xmind 檔案。讀取現有圖時先說明結構與重點,再詢問是否匯出 Markdown。遵循使用者語言,清理檔名並明確輸出目錄;審閱包且限制其僅存取預期檔案。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 2491 | — | - |
| 2026-08 | 1936 | +16.2% | - |
| 2026-07 | 1666 | +22.6% | - |
| 2026-06 | 1359 | +12.4% | - |
| 2026-05 | 1209 | — | - |
| 2026-03 | 666 | — | - |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。
---
name: xmind
description: Generate and read XMind (.xmind) files via the published xmind-generator-mcp MCP server (npm), with a chat-first UX.
metadata:
openclaw:
emoji: "🧠"
requires:
bins: ["mcporter", "npx"]
install:
- id: npm kind: note
label: "Uses npx [email protected] (no separate install needed)"
---
# xmind 🧠
Generate and read **XMind** `.xmind` files using the published MCP server `xmind-generator-mcp` (npm).
This skill is chat-first:
- “Generate an XMind for this (optionally: save to …)” → generates a `.xmind` and sends it back.
- “Read this XMind and tell me what it’s about” → explains the map first, then offers a Markdown export.
## When to use
- User wants: “generate an XMind file from this outline / plan / PRD / test plan”.
- Output should be a real `.xmind` file that opens in XMind.
## Input format (for generation)
The MCP tool `generate-mind-map` accepts **Schema A** JSON:
```json
{
"title": "Root topic",
"filename": "mindmap-name-no-date",
"topics": [
{
"title": "Topic title (keep core info in the title)",
"note": "Optional: use sparingly; only when the title would be too long",
"labels": ["optional"],
"markers": ["Arrow.refresh"],
"children": [{"title": "Child topic"}]
}
]
}
```
## How the assistant should call the MCP (stdio via mcporter)
### Generate XMind
Use `npx [email protected]` as the MCP server command:
```bash
mcporter call --stdio "npx -y [email protected]" generate-mind-map --args '{...}'
```
### Read XMind (Markdown export)
```bash
mcporter call --stdio "npx -y [email protected]" read-mind-map --args '{"inputPath":"/path/to/file.xmind","style":"A"}'
```
## Read behavior in chat (UX requirement)
When a user sends an `.xmind` file and asks to “read/understand” it:
1) First, explain in detail what the mind map is about (summary + structure + key points + actionable items + gaps).
2) Only after that, ask whether the user wants an export.
3) If the user wants an export, default to **Markdown**.
- `generate --output` can be a directory (recommended) or a full `.xmind` path.
- If outputPath is omitted, the MCP server defaults to its configured `outputPath` environment variable (see below).
## Chat-first workflow (what the assistant should do)
Trigger phrases:
- “Generate an XMind for this” / “Make an XMind from this”
- “Read this XMind” / “Summarize this XMind”
Language rule (important):
- If the user does **not** explicitly specify the language of the generated mind map, **match the language of the user’s request**.
- Example: user asks in Chinese → generate Chinese topic titles.
- Example: user asks in English → generate English topic titles.
- Only switch languages if the user explicitly asks (e.g. “generate in English”).
Filename rule (important):
- If the user provides a filename/path, use it.
- If the user does **not** provide a filename:
- Default filename should follow the user’s request language.
- For Chinese: use short hyphen style, **no date** (e.g. `one-day-trip-detailed` in Chinese characters, but keep it short).
- For English: use a short slug, no date (e.g. `hong-kong-1-day-itinerary`).
- Always sanitize invalid filename characters: `\\ / : * ? \" < > |` → replace with `-`.
Steps:
1) Parse whether the user specified a save location/path.
- If specified, use that.
- If not specified, default to `~/Desktop`.
2) Determine output language:
- If user specified language → follow it.
- Else → match the user’s message language.
3) Convert the user’s content into Schema A JSON (in the chosen language).
- Keep it reasonably sized (avoid thousands of nodes in one go).
- Use XMind enrichment elements when helpful (but keep titles informative):
- `note`: **use sparingly**. Only put content in `note` when it would make the topic title too long or noisy. If the content is core to the plan, keep it in the title instead of hiding it in `note`.
- `labels`: add lightweight categorization (e.g. must-do/optional/rainy-day/budget/family-friendly).
- `relationships`: **sparingly** (mode A) — only for truly cross-branch links that add clarity.
4) Write the JSON to a temp file, e.g. `/tmp/xmind-<ts>.json`.
5) Call the MCP tool `generate-mind-map` via mcporter stdio (`npx [email protected]`).
Capture/compute the output file path.
6) **Send the generated `.xmind` back in chat as an attachment**.
7) Optionally also tell the user where it was saved on disk.
把長文字、文件與網頁內容壓縮成要點和關鍵詞的摘要工具。
透過 IMA OpenAPI 管理筆記與知識庫內容。
規定如何為網頁請求選擇合適工具的必讀指引。
呼叫百度 AI 搜尋介面做網頁檢索的技能。
用 uvx 直接呼叫 markitdown,把各類檔案轉成 Markdown。
面向 OpenClaw 的預設網頁搜尋,即時檢索多個引擎。
用 DuckDuckGo 介面做網頁、新聞、圖片與影片檢索的技能。
檢索並發現可用 OpenClaw 技能的技能。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。