goodqunbot

goodqunbot is a skill for Claude Code, Codex from ImGoodBai/goodable. It costs 41 tokens per session (1,802 once invoked), scanned A, original, MIT.

A Windows-only assistant for reading recent WeChat messages and sending text messages through the logged-in WeChat PC client. It works with individual contacts and group chats.

In plain words
What is it for?
Use it to fetch recent messages with senders, timestamps, and content, or send a text to a contact or group. It requires Windows 10 or 11, WeChat for PC, and a logged-in account.
Why use it?
It lets you retrieve or send messages through an AI chat instead of manually navigating WeChat for each request.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to fetch recent messages with senders, timestamps, and content, or send a text to a contact or group. It requires Windows 10 or 11, WeChat for PC, and a logged-in account.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/imgoodbai/goodable/goodqunbot
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 ImGoodBai/goodable --skill goodqunbot
Clone the repo
git clone --depth 1 https://github.com/ImGoodBai/goodable

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 goodqunbot

README.md
[![agentmods](https://agentmods.dev/badge/skills/imgoodbai/goodable/goodqunbot/github.svg)](https://agentmods.dev/skills/imgoodbai/goodable/goodqunbot)
Your own site
<a href="https://agentmods.dev/skills/imgoodbai/goodable/goodqunbot"><img src="https://agentmods.dev/badge/skills/imgoodbai/goodable/goodqunbot/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 goodqunbot

Your own site · 80×15
<a href="https://agentmods.dev/skills/imgoodbai/goodable/goodqunbot"><img src="https://agentmods.dev/badge/skills/imgoodbai/goodable/goodqunbot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,802 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.
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 $0.00041 $0.01802
Opus 5.5 $0.00016 $0.00721
Sonnet 5.5 $0.00008 $0.00360
Haiku 4.5 $0.00004 $0.00180

Measured 2mo ago against content hash c54e835f8681, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

goodqunbot 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 2mo ago.

The scan reads SKILL.md. This mod also ships 11 executable files (app/__init__.py, app/database.py, app/main.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/goodqunbot/SKILL.md · 239 lines

How it starts

The opening of the file, as written. The whole thing — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.

微信消息助手 (WeChat Message Assistant)

This skill enables AI to interact with WeChat directly through AI chat, providing two core capabilities: retrieving recent messages and sending messages to contacts or groups.

Platform Requirements

  • OS: Windows 10/11 only
  • WeChat: WeChat PC client must be installed, running, and logged in
  • Python: Python 3.11+ (automatically handled by Goodable)

Core Capabilities

1. Retrieve Recent Messages

Fetch the last 10-15 messages from any WeChat contact or group chat.

What you can ask:

Get the last 15 messages from "张三"
Show me recent messages from "Product Team" group
Retrieve messages from "李四", last 10 only

What AI will do:

  • Opens the specified chat in WeChat
  • Retrieves the requested number of messages (default: 15, max: 100)
  • Returns messages with timestamp, sender, and content
  • Formats as structured JSON for easy parsing

2. Send Messages

Send a text message to any WeChat contact or group chat.

What you can ask:

Send "Meeting at 3pm" to "张三"
Message "Product Team" group: "Release notes updated"
Tell "李四": "Please review the document"

What AI will do:

  • Opens the specified chat in WeChat
  • Sends the message content
  • Confirms successful delivery

How to Use

Prerequisites

Before using this skill, ensure:

  1. WeChat PC client is running
  2. You are logged into your WeChat account
  3. The contact/group name you specify exists in your WeChat

Example Usage

Scenario 1: Check messages from a colleague

User: "帮我看一下张三最近给我发了什么消息"
AI: [Runs get_messages.py script]
AI: "张三最近的5条消息:
1. [2024-01-28 10:30] 张三: 会议资料已发送
2. [2024-01-28 11:00] 张三: 请查收
..."

Scenario 2: Send a message

User: "给产品群发个消息:今天下午3点开会"
AI: [Runs send_message.py script]
AI: "消息已成功发送到产品群"

Instructions for AI

When the user requests WeChat message operations:

1. Retrieve Messages

Run the get_messages.py script:

python scripts/get_messages.py "<Contact/Group Name>" [count]

Read the full file on GitHub · 239 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. 2mo ago First seen · 239 lines · 41 tokens per session scan A c54e835f8681

Subscribe to this mod's changes

goodqunbot is a skill published in the GitHub repository ImGoodBai/goodable (196 stars, last pushed 9mo ago), licensed MIT. It adds 41 tokens to every session and 1,802 once invoked, about $0.0002 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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