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Install in OpenClaw
/install wechat-talk
Description
Windows 电脑端微信消息自动发送技能，通过键盘模拟给指定联系人发送消息。快捷命令：wt
Usage Guidance
This skill appears to do what it says (simulate keyboard to send WeChat messages), but I recommend caution: 1) Verify the package origin — _meta.json and .clawhub/origin.json metadata differ from the registry metadata (ownerId/slug mismatch). 2) Inspect and remove any unnecessary dependencies (pytesseract, opencv) before installing — they increase attack surface. 3) Be aware server.py runs a JSON-RPC stdin/stdout loop that allows programmatic calls to send messages; do not allow autonomous model invocation or untrusted processes to call it if you don't want unattended sending. 4) Review any local test_config.json before running (it can change recipients). 5) Run first in a safe/test environment and observe behavior; avoid running while you are actively using the machine (the tool injects keystrokes). If you need help verifying the metadata or trimming dependencies, obtain the original upstream source or ask the publisher for clarification before installing.
Capability Analysis
Type: OpenClaw Skill
Name: wechat-talk
Version: 1.0.2
The skill bundle provides automated WeChat messaging functionality for Windows using GUI automation libraries like pyautogui and pyperclip. The implementation in server.py and send_batch.py strictly follows the stated purpose of simulating keyboard inputs (Ctrl+F, Ctrl+V, Enter) to search for contacts and send messages. There is no evidence of data exfiltration, unauthorized network access, or malicious prompt injection in SKILL.md.
Capability Assessment
Purpose & Capability
Functionality in send_batch.py and server.py matches the description: keyboard simulation (pyautogui/pyperclip) to open WeChat, search contacts, paste and send messages. However, requirements.txt includes OCR/Computer Vision packages (pytesseract, opencv-python) that are not used by the provided code, which is disproportionate to the stated simple keyboard-simulation purpose. Also package/owner metadata in _meta.json and .clawhub/origin.json do not match the registry metadata (different ownerId and slug), which is inconsistent with the claimed source.
Instruction Scope
SKILL.md and scripts instruct the agent/user to run local Python scripts that will activate the WeChat window and simulate keystrokes — this is appropriate for the stated task. The code reads/writes a local queue file (send_queue.json) and may read test_config.json if present. There are no instructions to read unrelated user files or environment variables. Important: server.py implements a JSON-RPC stdin/stdout tool interface so an agent/process can call wechat_send_message and wechat_get_status programmatically; that enables silent/autonomous sending of messages if invoked by an agent or another process.
Install Mechanism
No install spec in registry (instruction-only), so nothing is automatically downloaded. A requirements.txt is included that pulls several third-party Python packages. The presence of unused heavy deps (pytesseract, opencv-python) increases attack surface and is not justified by SKILL.md or code; this is a maintenance/security concern but not direct evidence of maliciousness.
Credentials
The skill requests no environment variables, credentials, or external endpoints. That is proportionate to its purpose of local GUI automation. No secrets appear to be requested or used.
Persistence & Privilege
The skill exposes a long-running MCP-style tool loop (reads JSON requests on stdin and performs actions). With model invocation enabled (default), an agent could call the tool to send messages without explicit user prompts. Autonomous invocation alone isn’t always a problem, but combined with metadata inconsistencies and unexplained dependencies it raises the risk that the skill could be used to send messages unexpectedly. always:false mitigates some risk, but you should treat enabling autonomous calls carefully.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install wechat-talk - After installation, invoke the skill by name or use
/wechat-talk - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.2
- Added new files: __pycache__/server.cpython-314.pyc, input_verify.png, result.png, and verify.png.
- Removed test_config.json.
- No user-facing functional changes described in SKILL.md.
- Likely enhancements for verification and result visualization with newly added images.
v1.0.1
No file changes detected in this version.
- No updates or modifications were made to code or documentation.
- Version remains unchanged in all files.
v1.0.0
Summary: Major update with new features, improved usage, and better efficiency.
- 全新发布，版本 2.0.0，支持 Windows 微信消息自动发送
- 新增批量发送、快捷命令 wt、多联系人优化流程
- 使用全键盘模拟方式，无需微信 API
- 增强错误提示与格式校验，避免格式错误
- 丰富使用文档，详细说明各使用方式和注意事项
Metadata
Frequently Asked Questions
What is 给微信的联系人或者群发送信息?
Windows 电脑端微信消息自动发送技能，通过键盘模拟给指定联系人发送消息。快捷命令：wt. It is an AI Agent Skill for Claude Code / OpenClaw, with 205 downloads so far.
How do I install 给微信的联系人或者群发送信息?
Run "/install wechat-talk" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is 给微信的联系人或者群发送信息 free?
Yes, 给微信的联系人或者群发送信息 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does 给微信的联系人或者群发送信息 support?
给微信的联系人或者群发送信息 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created 给微信的联系人或者群发送信息?
It is built and maintained by 返璞归真 (@zhangpuego123); the current version is v1.0.2.
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