10-of-my-most-popular-text-to-image-series-prompts-78b0897e
generate a bunch of images, then you curate the results to handpick the best ones
Generate and read XMind (.xmind) files via the published xmind-generator-mcp MCP server (npm), with a chat-first UX.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install bangyizhang/xmind-skill打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Generate and read XMind .xmind files using the published MCP server xmind-generator-mcp (npm).
This skill is chat-first:
.xmind and sends it back..xmind file that opens in XMind.The MCP tool generate-mind-map accepts Schema A 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"}]
}
]
}
Use npx xmind-generator-mcp@0.1.2 as the MCP server command:
mcporter call --stdio "npx -y xmind-generator-mcp@0.1.2" generate-mind-map --args '{...}'
mcporter call --stdio "npx -y xmind-generator-mcp@0.1.2" read-mind-map --args '{"inputPath":"/path/to/file.xmind","style":"A"}'
When a user sends an .xmind file and asks to “read/understand” it:
generate --output can be a directory (recommended) or a full .xmind path.outputPath environment variable (see below).Trigger phrases:
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
# 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 xmind-generator-mcp@0.1.2` as the MCP server command:
```bash
mcporter call --stdio "npx -y xmind-generator-mcp@0.1.2" generate-mind-map --args '{...}'
```
### Read XMind (Markdown export)
```bash
mcporter call --stdio "npx -y xmind-generator-mcp@0.1.2" 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:
- “Gene...generate a bunch of images, then you curate the results to handpick the best ones
generate a bunch of images, then you curate the results to handpick the best ones
Productivity system based on Maya calendar with 13 natural tones for project management and personal development
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.