技能详情（站内镜像，无评论）
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v1.0.8
统计：⭐ 1 · 748 · 10 current installs · 10 all-time installs
⭐ 1
安装量（当前） 10
🛡 VirusTotal ：可疑 · OpenClaw ：可疑
Package：autogame-17/feishu-sticker
安全扫描（ClawHub）
- VirusTotal ：可疑
- OpenClaw ：可疑
OpenClaw 评估
The skill mostly does what it claims (upload/send Feishu stickers) but its declared metadata, runtime instructions, and file I/O/credential usage are inconsistent and incomplete — review before installing or providing credentials.
目的
The skill's name/description match the code (uploading and sending images to Feishu). However the published metadata lists no required environment variables or credentials, while the code (send.js) requires FEISHU_APP_ID and FEISHU_APP_SECRET and will exit if they are not present. find.js also contains a hard-coded home path (/home/crishaocredits/...) instead of a generic default, which looks like leftover developer-specific configuration. The…
说明范围
SKILL.md describes sticker directory and npm install but does not document the FEISHU_APP_ID/FEISHU_APP_SECRET requirement or the skill's behavior of reading ../../.env and writing token and image-key cache files under a 'memory' path. The code will: read arbitrary files (via --file), create/modify directories (sticker dir, memory cache), delete original GIFs if they are in the sticker dir, and upload chosen files to Feishu. Uploading arbitrar…
安装机制
There is no remote download URL or installer; dependencies are standard npm packages (commander, dotenv, ffmpeg-static). The package-lock.json points to npm registry packages. The ffmpeg-static dependency runs an install script (normal for that package) and is GPL-licensed; this is expected for GIF->WebP conversion. No high-risk custom download URLs are present.
证书
Registry metadata declares no required env vars, but send.js requires FEISHU_APP_ID and FEISHU_APP_SECRET (and loads ../../.env). The code will read environment variables outside what SKILL.md documents and will write token and image-key caches into workspace-level memory paths (e.g., '../../memory/feishu_token.json'). That mismatch is a red flag — credentials are required but not advertised, and the skill will access and persist authenticatio…
持久
The skill writes token and image-key caches to a shared 'memory' location (TOKEN_CACHE_FILE '../../memory/feishu_token.json' and an image key cache). It may create or delete files under the user's sticker directory and the memory directory. It does not set always:true and does not modify other skills' configs, but the undocumented read/write of ../../.env and '../../memory' may give it persistent data stored on disk beyond the skill's installa…
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「feishu-sticker」。简介：Send images as native Feishu stickers with auto-upload, caching by hash, GIF-to…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/autogame-17/feishu-sticker/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: feishu-sticker
description: Send images as native Feishu stickers. Features auto-upload, caching, and GIF-to-WebP conversion.
tags: [feishu, lark, sticker, image, fun]
---
# Feishu Sticker Skill
Sends a sticker (image) to a Feishu user or group.
Automatically uploads the image to Feishu (caching the `image_key` via MD5), converts GIFs to WebP for efficiency, and supports smart search.
## Features
- **Auto-Upload**: Uploads local images to Feishu CDN on demand.
- **Caching**: Caches `image_key` by file hash to avoid re-uploading.
- **Optimization**: Auto-converts GIFs to WebP (via `ffmpeg-static`) and compresses large images (>5MB).
- **Smart Search**: Find stickers by `--query` or `--emotion`.
## Usage
```bash
# Send random sticker
node skills/feishu-sticker/send.js --target "ou_..."
# Send specific file
node skills/feishu-sticker/send.js --target "ou_..." --file "/path/to/image.jpg"
# Search and send
node skills/feishu-sticker/send.js --target "ou_..." --query "angry cat"
node skills/feishu-sticker/send.js --target "ou_..." --emotion "happy"
```
## Setup
1. Put your stickers in `~/.openclaw/media/stickers/` (or set `STICKER_DIR`).
2. Install dependencies: `npm install` (requires `axios`, `commander`, `ffmpeg-static`, `form-data`, `dotenv`).