dingtalk_channel_connect

dingtalk_channel_connect is a skill for Claude Code, Codex from agentscope-ai/QwenPaw. It costs 78 tokens per session (2,328 once invoked), scanned A, original, Apache-2.0.

A browser-based procedure for connecting a QwenPaw bot to DingTalk, a workplace messaging platform. It covers creating or configuring the application and publishing the finished bot.

In plain words
What is it for?
Use it to create a DingTalk application, configure its bot, upload its images, bind it to a QwenPaw channel, and publish it.
Why use it?
It guides the setup through login pauses, required image formats, and the final publishing step needed for configuration changes to take effect.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for qwenpaw. Also seen: built for qwenpaw.

Good fit Use it to create a DingTalk application, configure its bot, upload its images, bind it to a QwenPaw channel, and publish it.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/agentscope-ai/qwenpaw/dingtalk_channel-zh
About the project

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.

agentscope-ai/QwenPaw · 34,809 stars · on GitHub · qwenpaw.agentscope.io

Install

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.

Any agent
npx skills add agentscope-ai/QwenPaw --skill dingtalk_channel-zh
Clone the repo
git clone --depth 1 https://github.com/agentscope-ai/QwenPaw

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for dingtalk_channel_connect

README.md
[![agentmods](https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw/dingtalk_channel-zh/github.svg)](https://agentmods.dev/skills/agentscope-ai/qwenpaw/dingtalk_channel-zh)
Your own site
<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.

agentmods 80×15 button for dingtalk_channel_connect

Your own site · 80×15
<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>
Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,328 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. ✓ AI security review Fable 5.1 · 6 Sept 2026 📄 Read the review Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00078 $0.02328
Opus 5 $0.00039 $0.01164
Sonnet 5 $0.00016 $0.00466
Haiku 4.5 $0.00008 $0.00233

Measured 13d ago against content hash 34e5f2f67bd9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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 13d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

src/qwenpaw/agents/skills/dingtalk_channel-zh/SKILL.md · 194 lines

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

  1. 必须使用可视浏览器模式启动:
{"action": "start", "headed": true}
  1. 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。
  2. 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:

  1. 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
  2. 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,1:12MB 以内,无圆角。
    • 机器人消息预览图:格式 png/jpeg/jpg,不超过 2MB
  3. 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
  4. 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。”
  1. 若用户提供本地路径,直接用于上传。
  2. 若用户提供图片 link,先下载到本地临时文件,再执行上传。
  3. 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
  4. 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

  1. file_uploadpaths_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\"]"
}
  1. 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。

  2. 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.
  3. 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"
  4. 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

  1. 可视模式启动浏览器(headed: true
  2. 打开 https://open-dev.dingtalk.com/
  3. 调用 snapshot 判断是否需要登录

Read the full file on GitHub · 194 lines

Changes

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.

  1. 13d ago First seen · 194 lines · 78 tokens per session scan A 34e5f2f67bd9

Subscribe to this mod's changes

dingtalk_channel_connect is a skill published in the GitHub repository agentscope-ai/QwenPaw (34,809 stars, last pushed yesterday), licensed Apache-2.0. It adds 78 tokens to every session and 2,328 once invoked, about $0.0004 per session on Opus 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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