Generate and edit Draw.io, Mermaid, and Excalidraw diagrams from natural language using a structured JSON spec.
by nssa.io1.0k installs47 stars
Documents
tibetan-buddhist-product-article-generator
Try it读取 ~/.openclaw/workspace/tibetanDraft/ 中的Markdown，识别藏传佛教产品主题，生成约1000字简体中文文章到 ~/.openclaw/workspace/tibetanProc/。 只写藏传佛教，事实需网络核验，含至少3章节+主图+章节图。文件名用时间戳格式。 Read...
What it does
Tibetan Buddhist Product Article Generator
The skill document
Tibetan Buddhist Product Article Generator
🎯 Purpose
自动生成符合藏传佛教标准的中文产品文章，包含网络事实核验和藏式图像。
📂 Input/Output Paths
输入目录: ~/.openclaw/workspace/tibetanDraft/
输出目录: ~/.openclaw/workspace/tibetanProc/
文件命名规则 (必须严格遵守):
yymmddHHMM_主体名.md
yymmddHHMM_main.png # 主图
yymmddHHMM_section1.png # 章节1图
yymmddHHMM_section2.png # 章节2图
🔄 完整执行流程
1. 初始化检查
检查 ~/.openclaw/workspace/tibetanDraft/ 是否存在 检查是否有 .md 文件 如果目录不存在或为空 → 报错 "草稿目录为空，请先放入输入文件" 如果多个文件 → 读取最新的一个
2. 主题识别
从输入文件提取藏传佛教产品主题，如：唐卡、法器、佛像、经书等。
3. 网络研究 (必须)
搜索查询示例： "Tibetan Buddhism [产品] history verified" "Tibetan [产品] traditional use past present" "Tibetan Buddhism [产品] materials facts"
4. 文章生成规则
- 语言: 口语化、非正式简体中文
- 长度: 约1000字
- 章节 (至少3个):
- 藏族历史与藏传佛教历史相关背景
- 产品信息核验 (材料、制作、用途)
- 藏族过去和现在的用法
- 对拥有者的宗教文化身心价值 (不夸大)
- 事实原则: 未验证的信息写"资料显示"或"未确认"
5. 图像生成
主图提示: "Traditional Tibetan Buddhist [产品] in authentic thangka style, rich colors, gold details, temple setting" 章节图提示: "Tibetan [场景] featuring [产品], authentic religious art style" 输出: PNG, 同目录, 时间戳文件名
6. 输出模板
# [产品名称]
摘要
...
## 第一节：历史背景
...
## 第二节：产品信息
...
(以此类推)
⚠️ 错误处理与回退
| 错误场景 | 处理方式 | 输出文件 |
|---|---|---|
| 草稿目录不存在 | 创建目录并提示 | 无 |
| 无输入文件 | 输出说明文件 | yymmddHHMM_usage.md |
| 主题无法识别 | 列出可能主题，等待确认 | yymmddHHMM_topics.md |
| 网络搜索失败 | 使用本地知识 + 标记"需进一步验证" | 正常输出 + 警告 |
| 图像生成失败 | 输出无图版本 + 记录日志 | yymmddHHMM_log.txt |
🧪 测试用例
输入文件: test_tibetanDraft/thangka_draft.md
我想写一篇关于唐卡的文章...
预期输出:
2604071901_thangka.md (约1000字) 2604071901_main.png 2604071901_section1.png (历史) 2604071901_section2.png (产品信息) ...
📋 元数据文件 (自动生成)
每个输出文件夹会附带:
skill-run.json: { "timestamp": "2604071901", "input_file": "原文件名", "product": "识别的产品", "word_count": 1024, "images_generated": 4, "research_sources": ["web:1", "web:11", ...] }
🚀 自动化运行参数
--dry-run: 只检查不生成 --product=强制指定产品名 --draft=指定输入文件 --output-dir=自定义输出目录
此技能符合 ClawHub 发布标准，已包含完整错误处理、测试用例和自动化模板。
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