How do I install the Feishu Rich Card skill?

Run npx skillmds@latest add biotender-max/feishu-rich-card in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Which AI agents work with Feishu Rich Card?

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Is Feishu Rich Card free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Feishu Rich Card?

BioTender-max (@biotender-max) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Feishu Rich Card by biotender-max — Agent Skill

Name: Feishu Rich Card
Author: BioTender-max

Feishu Rich Card

Send rich interactive cards with embedded images in Feishu group chats. Use when reporting progress, sharing analysis results, or presenting any content that benefits from mixed text+image layout in Feishu. Combines SVG UI templates (or matplotlib/PIL charts) with Feishu Card Kit API.

BioTender-max Updated Sep 17, 2026

File contents

Feishu Rich Card — 飞书图文混排卡片

在飞书群聊中发送图文并茂的交互式卡片，用于汇报进展、展示分析结果、项目状态等。

When to Use

汇报任务进展、项目状态
展示数据分析结果（图表 + 解读）
发送研究简报、阶段性成果
任何需要图文混排的飞书消息

Architecture

生成图片(SVG→PNG / matplotlib / PIL)
        ↓
上传图片到飞书 → 获取 image_key
        ↓
构造 Card JSON (schema 2.0) → 嵌入 img 元素 + markdown 元素
        ↓
调用飞书 API 发送 interactive 消息

Workflow

Step 1: Prepare Images

图片来源可以是：

SVG UI 模板 → 用 svg-ui-templates skill 生成 SVG → cairosvg 转 PNG
matplotlib/seaborn → 直接 savefig 为 PNG
PIL/Pillow → 程序化生成图片
已有文件 → 直接使用本地 PNG/JPG

Step 2: Upload & Send

使用 references/send_card.py 中的辅助函数：

# 完整用法参见 references/send_card.py
from send_card import FeishuCardSender

sender = FeishuCardSender()  # 自动读取 openclaw.json 凭证

# 发送图文卡片
sender.send_rich_card(
    chat_id="oc_xxx",
    title="📊 分析报告",
    elements=[
        {"type": "markdown", "content": "## 结果摘要\n\n发现 **3 个**显著差异基因"},
        {"type": "image", "path": "/tmp/volcano_plot.png", "alt": "火山图"},
        {"type": "markdown", "content": "> Gene X: FC=2.5, p<0.001"},
        {"type": "hr"},
        {"type": "image", "path": "/tmp/heatmap.png", "alt": "热图"},
        {"type": "markdown", "content": "**结论：** 样本间差异显著，建议进一步验证。"},
    ],
    header_template="blue"  # blue/indigo/green/red/purple/violet/wathet/turquoise/yellow/grey
)

Step 3: Quick One-liner (for simple cases)

sender.send_image_report(
    chat_id="oc_xxx",
    title="🧬 单细胞分析完成",
    intro="UMAP 降维完成，共识别 12 个细胞群：",
    image_path="/tmp/umap.png",
    conclusion="Cluster 5 为目标细胞群，marker: CD8A, GZMB, PRF1",
    header_template="indigo"
)

Card Elements Reference

Element	Tag	说明
Markdown	`markdown`	支持加粗、斜体、链接、列表、引用块、代码块
Image	`img`	需要 `image_key`（上传后获取）
Divider	`hr`	水平分割线
Column Set	`column_set`	多列并排布局
Note	`note`	底部灰色备注

Header Templates (颜色)

blue wathet turquoise green yellow orange red carmine violet purple indigo grey

Key Rules

图片必须先上传到飞书获取 image_key，不能用 URL
Card schema 必须是 "2.0"
每张卡片最多 50 个元素
图片建议宽度 600-1200px，飞书会自动缩放
markdown 中不能嵌入图片，图片必须是独立的 img 元素
发送后 OpenClaw 的正常回复会重复，用 NO_REPLY 避免

Integration with SVG UI Templates

当需要专业级可视化时，结合 svg-ui-templates skill：

# 1. 生成 SVG（用模板或自定义）
# 2. 转 PNG
python3 -c "import cairosvg; cairosvg.svg2png(url='report.svg', write_to='report.png', output_width=2400)"
# 3. 用本 skill 上传并发送卡片

Default Chat ID

通过环境变量配置：FEISHU_DEFAULT_CHAT_ID（在 .env 中设置）

---name: feishu-rich-carddescription: Send rich interactive cards with embedded images in Feishu group chats. Use when reporting progress, sharing analysis results, or presenting any content that benefits from mixed text+image layout in Feishu. Combines SVG UI templates (or matplotlib/PIL charts) with Feishu Card Kit API.---# Feishu Rich Card — 飞书图文混排卡片在飞书群聊中发送**图文并茂**的交互式卡片，用于汇报进展、展示分析结果、项目状态等。## When to Use- 汇报任务进展、项目状态- 展示数据分析结果（图表 + 解读）- 发送研究简报、阶段性成果- 任何需要图文混排的飞书消息## Architecture```生成图片(SVG→PNG / matplotlib / PIL) ↓上传图片到飞书 → 获取 image_key ↓构造 Card JSON (schema 2.0) → 嵌入 img 元素 + markdown 元素 ↓调用飞书 API 发送 interactive 消息```## Workflow### Step 1: Prepare Images图片来源可以是：- **SVG UI 模板** → 用 `svg-ui-templates` skill 生成 SVG → cairosvg 转 PNG- **matplotlib/seaborn** → 直接 savefig 为 PNG- **PIL/Pillow** → 程序化生成图片- **已有文件** → 直接使用本地 PNG/JPG### Step 2: Upload & Send使用 `references/send_card.py` 中的辅助函数：```python# 完整用法参见 references/send_card.pyfrom send_card import FeishuCardSendersender = FeishuCardSender() # 自动读取 openclaw.json 凭证# 发送图文卡片sender.send_rich_card( chat_id="oc_xxx", title="📊 分析报告", elements=[ {"type": "markdown", "content": "## 结果摘要\n\n发现 **3 个**显著差异基因"}, {"type": "image", "path": "/tmp/volcano_plot.png", "alt": "火山图"}, {"type": "markdown", "content": "> Gene X: FC=2.5, p<0.001"}, {"type": "hr"}, {"type": "image", "path": "/tmp/heatmap.png", "alt": "热图"}, {"type": "markdown", "content": "**结论：** 样本间差异显著，建议进一步验证。"}, ], header_template="blue" # blue/indigo/green/red/purple/violet/wathet/turquoise/yellow/grey)```### Step 3: Quick One-liner (for simple cases)```pythonsender.send_image_report( chat_id="oc_xxx", title="🧬 单细胞分析完成", intro="UMAP 降维完成，共识别 12 个细胞群：", image_path="/tmp/umap.png", conclusion="Cluster 5 为目标细胞群，marker: CD8A, GZMB, PRF1", header_template="indigo")```## Card Elements Reference| Element | Tag | 说明 ||---------|-----|------|| **Markdown** | `markdown` | 支持加粗、斜体、链接、列表、引用块、代码块 || **Image** | `img` | 需要 `image_key`（上传后获取） || **Divider** | `hr` | 水平分割线 || **Column Set** | `column_set` | 多列并排布局 || **Note** | `note` | 底部灰色备注 |## Header Templates (颜色)`blue` `wathet` `turquoise` `green` `yellow` `orange` `red` `carmine` `violet` `purple` `indigo` `grey`## Key Rules1. **图片必须先上传**到飞书获取 `image_key`，不能用 URL2. **Card schema 必须是 `"2.0"`**3. **每张卡片最多 50 个元素**4. 图片建议宽度 600-1200px，飞书会自动缩放5. markdown 中**不能嵌入图片**，图片必须是独立的 `img` 元素6. 发送后 OpenClaw 的正常回复会重复，用 `NO_REPLY` 避免## Integration with SVG UI Templates当需要专业级可视化时，结合 `svg-ui-templates` skill：```bash# 1. 生成 SVG（用模板或自定义）# 2. 转 PNGpython3 -c "import cairosvg; cairosvg.svg2png(url='report.svg', write_to='report.png', output_width=2400)"# 3. 用本 skill 上传并发送卡片```## Default Chat ID通过环境变量配置：`FEISHU_DEFAULT_CHAT_ID`（在 `.env` 中设置）

Frequently asked questions