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Wechat Decrypt

Community
freanocank
wechat-decrypt

Read, search, summarize, export, and transcribe a user's own local WeChat 4.x history on macOS or Windows; diagnose setup and re-extract the device key after a WeChat update. Use for WeChat messages, chats, contacts, and local archives. Do not use for remote accounts or devices the user is not authorized to access.

Overview

Publisherfreanocank
Repositorywechat-decrypt
Skill namewechat-decrypt
Stars
83
Forks
43
Bundled files
122
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 122 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by freanocank on GitHub. Read the source before you install it.

Installation

Install the Wechat Decrypt AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/freanocank/wechat-decrypt/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/freanocank/wechat-decrypt.git \
  .claude/skills/wechat-decrypt
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wechat Decrypt in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Wechat Decrypt on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Wechat Decrypt is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

WeChat local history

Operate only on local WeChat data the user is authorized to access. Keep keys, decrypted databases, voice caches, and exports local. Never print a raw key or include one in chat, logs, commands, or reports.

Resolve the runtime

Use the directory containing this SKILL.md as SKILL_DIR; never assume a fixed installation path.

  • macOS: prefer $SKILL_DIR/.venv/bin/python, otherwise python3.
  • Windows: prefer $SKILL_DIR\.venv\Scripts\python.exe, otherwise python.

Before reading chat data, run the read-only diagnostic:

bash
"$SKILL_DIR/.venv/bin/python" "$SKILL_DIR/scripts/common/doctor.py" --json

On Windows, use the equivalent venv Python path. Interpret fail as blocking and warn as optional/degraded:

  • key or database failure: read the matching platform reference below.
  • mcp warning: use the CLI fallback now; run platform setup only when MCP registration is needed.
  • voice-backend warning: ordinary export works; install the optional platform voice stack only for transcription.
  • voice-model warning: ordinary export still works. Do not download the model without user approval.

Route the request

IntentPreferred action
List chats or groupswechat_list_chats
Read one chatwechat_read_chat
Search all chatswechat_search_messages
Review recent activitywechat_recent_messages
Summarize recent chats and action itemswechat_chat_summary
Review pats, recalls, group changes, payments, or callswechat_system_events; filter with a stable code or Chinese label
Review shared music, videos, Channels, mini programs, files, or linksUse normal read/search/summary tools; inspect the structured app object in CLI JSON when exact metadata matters
Statistics, media, or a received documentCLI stats, media, or openfile
Export history or transcribe voiceRead references/export-transcription.md
Missing chats, a missing shard, or a corrupted databaseRead references/db-repair.md
macOS setup, key failure, or WeChat updateRead references/macos.md
Windows setup, key failure, or WeChat updateRead references/windows.md

MCP is a thin optional facade. If it is unavailable, use the same logic through scripts/common/query.py and request JSON:

bash
"$PYTHON" "$SKILL_DIR/scripts/common/query.py" list --json
"$PYTHON" "$SKILL_DIR/scripts/common/query.py" read CONTACT -d 7 -n 50 --json
"$PYTHON" "$SKILL_DIR/scripts/common/query.py" search KEYWORD -d 30 -n 50 --json
"$PYTHON" "$SKILL_DIR/scripts/common/query.py" recent -d 3 -n 100 --json
"$PYTHON" "$SKILL_DIR/scripts/common/query.py" summary -d 3 --json
"$PYTHON" "$SKILL_DIR/scripts/common/query.py" events -e pat -d 30 -n 100 --json

[我] means the account owner; [对方] means the peer. If contact matching is ambiguous, show the candidates and ask the user to choose; do not guess. Keep time windows and limits proportional to the request, and do not dump full history unless explicitly requested.

Operational invariants

  • Raw keys are 64 hexadecimal characters and are device-specific. macOS and Windows keys for the same account are not interchangeable.
  • macOS queries encrypted databases in place through SQLCipher, always read-only.
  • Windows first creates a local plaintext mirror under decrypted/, then queries it read-only. Treat that mirror as sensitive.
  • WeChat updates may invalidate extraction assumptions or require a new key. Run doctor.py before repeating extraction.
  • Voice transcription is offline after the model is cached. A first large-v3 download is about 3 GB and always requires user approval.
  • Type-49 app messages are parsed locally. Preserve their structured app metadata when answering questions about titles, creators, sources, URLs, files, mini programs, or Channels; unknown subtypes may still contain useful fields.
  • Setup migrates only missing private files from legacy installs. Switching an existing user-skill link requires the explicit platform upgrade flag and leaves a recoverable backup.
  • A damaged shard is quarantined into <name>.db.factory/ and is usually recoverable page by page. Never repair a live database in place: rebuild into a copy, verify it, and back up before restoring anything.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

and 62 more files.

Frequently asked questions

What does the Wechat Decrypt AI skill do?

Read, search, summarize, export, and transcribe a user's own local WeChat 4.x history on macOS or Windows; diagnose setup and re-extract the device key after a WeChat update. Use for WeChat messages, chats, contacts, and local archives. Do not use for remote accounts or devices the user is not authorized to access.

Why use Wechat Decrypt on TypingMind?

Because you install it once and use it with any model. Wechat Decrypt is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Wechat Decrypt in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/freanocank/wechat-decrypt/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Wechat Decrypt?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Wechat Decrypt?

As many as you like. As long as a model supports skills, you can use Wechat Decrypt with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Wechat Decrypt AI skill free?

Yes. It is published on GitHub by freanocank under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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