weclaw

name	weclaw
description	Sync selected WeChat desktop chats to JSON on the host, generate an optional LLM report, and answer questions from the captured messages.
metadata	{"openclaw":{"emoji":"🦞","os":["darwin","win32"],"requires":{"anyBins":["python3"]}}}

WeClaw (OpenClaw host skill)

WeChat must be the desktop app on the same machine as OpenClaw Gateway. This skill automates the UI; it does not work from a phone alone.

One-time setup on the host

1. Clone WeClaw next to your workspace or any fixed path. Set a durable env var (shell profile or OpenClaw skills.entries.weclaw.env):

   • WECLAW_ROOT = absolute path to the WeClaw git checkout (directory that contains run.sh).

2. Python venv (from WeClaw README):

   cd "$WECLAW_ROOT"
   python3 -m venv .venv
   ./.venv/bin/pip install -r requirements.txt
   

3. Copy config/config.json.example to config/config.json. Fill groups_to_monitor and either put openrouter_api_key in the file or export OPENROUTER_API_KEY (env overrides JSON when present per WeClaw config).

4. macOS: grant Accessibility to the app running Python (Terminal, iTerm, or the OpenClaw host). Windows: match elevation with WeChat if needed.

5. Install this skill into the active OpenClaw workspace skills/weclaw/ (the script uses openclaw skills list --json to find workspaceDir when openclaw is on PATH, or set OPENCLAW_WORKSPACE to override):

   "$WECLAW_ROOT/scripts/install_openclaw_skill.sh"
   

   Or copy {baseDir} (this skill’s directory) into your workspace skills/weclaw/ yourself. OpenClaw discovers skills/weclaw/SKILL.md.

Optional openclaw.json (JSON5) snippet so the agent always sees WECLAW_ROOT:

skills.entries.weclaw.env.WECLAW_ROOT = "/absolute/path/to/weclaw"

Run the capture + report pipeline

From the host shell (or schedule via OpenClaw cron / systemd / launchd calling the same command):

export WECLAW_ROOT="/absolute/path/to/weclaw"
export WECLAW_CONFIG_PATH="$WECLAW_ROOT/config/config.json"
cd "$WECLAW_ROOT"
./run.sh

With a non-default config path:

./run.sh /path/to/other-config.json

Stdout is the generated report text (or No matching messages found.). Structured chat exports are JSON files under output_dir from config (default output/).

Machine-readable status

After every run, WeClaw writes last_run.json inside the configured output_dir:

• ok — pipeline completed without exception
• message_json_paths — list of JSON files produced this run (may be empty)
• report_generated — whether algo_b ran
• error — set when ok is false (run still surfaces the exception afterward)

Use this file in automation to decide whether to notify the user or attach paths in a follow-up agent turn.

Answering user questions

When the user asks about WeChat content after a successful run:

1. Run weclaw-cua ask "<user question>" from WECLAW_ROOT. This reads last_run.json, ranks nearby message snippets across the captured JSON files, and returns cited context.
2. Answer only from the returned snippets. Prefer quoting chat facts with chat/sender/time; do not invent messages.
3. If the user explicitly asks about older history, rerun with --all-history and optional --chat "Name" filters.
4. If ranked snippets are insufficient, say what is missing and use weclaw-cua search, weclaw-cua history, or direct JSON reads as a follow-up.

If message_json_paths is empty, say that there were no captured chats this run and offer to run ./run.sh again.

Cron / nightly jobs

Point the scheduler at the host path only (Gateway must be able to execute on the machine where WeChat runs). Example: run bash -lc 'cd "$WECLAW_ROOT" && ./run.sh' at the desired time. OpenClaw’s cron tool can invoke the same command when the main session has cron enabled; see OpenClaw automation docs.