openclaw-network-diagnostics

# OpenClaw Network Diagnostics

## Overview

Run a pure network diagnostic worker from CLI to continuously monitor connectivity between:
1. OpenClaw runtime host
2. Telegram Bot API (`api.telegram.org`)
3. Personal Telegram client approximation via delivery verification cycles

Keep diagnostics isolated from OpenClaw LLM flow:
- Use no LLM calls.
- Consume no AI tokens.
- Run in independent async worker loops.

## Skill Files

- `scripts/netdiag.py`: standalone CLI worker (`run/start/stop/status/validate-config`)
- `references/config.example.json`: complete example configuration
- `references/example-log-entries.jsonl`: sample structured JSON logs
- `references/openclaw-integration.md`: integration patterns with pros/cons
- `references/ai-log-analysis.md`: workflow for later AI-based log analysis

## Prerequisites

Install and verify:
1. Python `3.11+`
2. macOS networking tools: `dig`, `ping`, `traceroute`
3. Telegram bot token and personal chat id

## Install

From skill root:

```bash
cd /Users/ivanbelugin/Documents/Connection\ Monitoring\ System/openclaw-network-diagnostics
python3 scripts/netdiag.py validate-config --config references/config.example.json
```

Create a real config file from the example and set real credentials:

```bash
cp references/config.example.json config.json
```

Then edit `config.json`:
- `telegram.bot_token`
- `telegram.personal_chat_id`

## Run Model

### Foreground mode (manual stop via Ctrl+C)

```bash
python3 scripts/netdiag.py run --config config.json --pid-file ./logs/netdiag.pid
```

Behavior:
- Start manually from CLI.
- Run continuously until manual stop.
- Print JSON summary to stdout on stop.
- Save summary to `logging.summary_file_path`.

### Background mode (non-blocking service)

```bash
python3 scripts/netdiag.py start --config config.json --pid-file ./logs/netdiag.pid
python3 scripts/netdiag.py status --pid-file ./logs/netdiag.pid
python3 scripts/netdiag.py stop --pid-file ./logs/netdiag.pid
```

Use this mode to avoid bl...