QwenPaw is a personal AI assistant that runs on a local machine or in the cloud and connects to multiple chat applications. It provides memory, file workspaces, multiple agents, skills, plugins, and integrations with language-model providers and external tools. The catalogue entries are skills that extend its capabilities.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add agentscope-ai/QwenPaw --skill dingtalk_channel-zhgit clone --depth 1 https://github.com/agentscope-ai/QwenPawWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agentscope-ai/qwenpaw/dingtalk_channel-zh)<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw/dingtalk_channel-zh"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/dingtalk_channel-zh/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw/dingtalk_channel-zh"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/dingtalk_channel-zh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00078 | $0.02328 |
| Opus 5.5 | $0.00031 | $0.00931 |
| Sonnet 5.5 | $0.00016 | $0.00466 |
| Haiku 4.5 | $0.00008 | $0.00233 |
Grade A, and why
dingtalk_channel_connect scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- dingtalk_channel_connect — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.
钉钉频道自动连接(可视浏览器)
此 skill 用于通过可视浏览器自动化完成钉钉应用创建与 QwenPaw channel 绑定。
强制规则
- 必须使用可视浏览器模式启动:
{"action": "start", "headed": true}
-
遇到登录关卡必须暂停:
- 若页面出现登录界面(如
登录、扫码登录、手机号/密码登录),立即停止自动操作。 - 明确提示用户先手动登录,再等待用户回复“登录好了/继续”。
- 未收到用户确认前,不得继续执行后续步骤。
- 若页面出现登录界面(如
-
任何应用配置变更都必须新建版本并发布后才生效:
- 配置完机器人相关信息后一定要发布机器人
- 不论是新建应用还是修改应用信息(名称、描述、图标、机器人配置等),最终都必须执行“创建新版本 + 发布”。
- 若未完成发布,不得宣称配置已生效。
执行前显著确认(必须先做)
在开始自动化点击前,先向用户发起一次“配置确认”,明确告知可自定义项、图片规范、默认值。建议使用如下结构化确认:
-
让用户可自定义以下字段:
- 应用名称
- 应用描述
- 机器人图标图片链接或本地路径
- 机器人消息预览图链接或本地路径
-
明确告知图片规范(显著提示):
- 机器人图标:仅支持 JPG/PNG,
240*240px以上,1:1,2MB以内,无圆角。 - 机器人消息预览图:格式
png/jpeg/jpg,不超过2MB。
- 机器人图标:仅支持 JPG/PNG,
-
明确告知默认值(用户不指定时自动采用):
- 应用名称:
QwenPaw - 应用描述:
Your personal assistant - 机器人图标:
https://img.alicdn.com/imgextra/i4/O1CN01M0iyHF1FVNzM9qjC0_!!6000000000492-2-tps-254-254.png - 机器人消息预览图:
https://img.alicdn.com/imgextra/i4/O1CN01M0iyHF1FVNzM9qjC0_!!6000000000492-2-tps-254-254.png
- 应用名称:
-
若用户未给任何自定义值,必须先明确回复:
- “将全部采用默认设置(QwenPaw / Your personal assistant / 默认图片)后继续执行。”
图片上传策略(link/path 都支持)
- 若用户提供本地路径,直接用于上传。
- 若用户提供图片 link,先下载到本地临时文件,再执行上传。
- 上传动作顺序必须是:
- 先点击页面上传入口(触发 chooser)
- 再调用
file_upload传入本地路径数组(paths_json)
- 若上传报错且判断为图片规格不符合(尺寸、比例、大小、格式):
- 立即暂停自动化
- 明确让用户手动上传符合规范的图片
- 用户确认“已上传/继续”后,从当前步骤继续后续流程
上传动作实战经验
file_upload的paths_json必须是“JSON 字符串数组”,注意转义:
{
"action": "file_upload",
"paths_json": "[\"xxx.png\"]",
"frame_selector": "iframe[src*=\"/fe/app?isHideOuterFrame=true\"]"
}
-
若页面在 iframe 内,建议优先带上
frame_selector,否则可能出现找不到上传控件或 chooser 未触发。 -
上传前必须先点击上传入口;若直接
file_upload会报:No chooser. Click upload then file_upload.
-
机器人图标区域的常见结构特征可用于定位(示例):
text: "* 机器人图标"button: "使用应用图标"button: "avatar"(通常内部有img "avatar")
-
当 snapshot 中同时出现“使用应用图标”和“avatar”时,优先点击
avatar按钮触发上传,再执行file_upload。
自动化流程
步骤 1:打开钉钉开发者后台
- 可视模式启动浏览器(
headed: true) - 打开
https://open-dev.dingtalk.com/ - 调用
snapshot判断是否需要登录
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 194 lines · 78 tokens per session scan A 34e5f2f67bd9
dingtalk_channel_connect is a skill published in the GitHub repository agentscope-ai/QwenPaw (36,385 stars, last pushed yesterday), licensed Apache-2.0. It adds 78 tokens to every session and 2,328 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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