Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Mrc Monitor
Real-time token monitoring for MRC canteen order system. Monitors Firebase Firestore for token status and notifies when orders are ready. Use when user sends commands like "mrc 73", "token 97", or "monitor 42" to monitor one or multiple canteen tokens. Handles multiple tokens simultaneously, sends independent notifications per token, and auto-exits when all tokens are ready.
skill openclawclawhub Free
Real-time token monitoring for MRC canteen order system. Monitors Firebase Firestore for token status and notifies when orders are ready. Use when user sends commands like "mrc 73", "token 97", or "monitor 42" to monitor one or multiple canteen tokens. Handles multiple tokens simultaneously, sends independent notifications per token, and auto-exits when all tokens are ready.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/monitor.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- wysh3
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
MRC Canteen Monitor
Monitor MRC canteen order tokens and notify when they're ready for pickup.
Quick Start
When user sends any command containing canteen tokens: Extract all token numbers from the message Start the background monitor script Respond immediately with confirmation
Command Recognition
Users may send tokens with various prefixes: "mrc 73" or "mrc 73 97 42" "token 73" or "token 73 97" "monitor 73" "check 73" (one-time check only)
Starting the Monitor
Extract all numbers from the user message and start the background monitor: python3 skills/mrc-monitor/scripts/monitor.py <platform> <channel_id> <token1> <token2> ... Where: platform: "telegram" or "discord" channel_id: Current channel identifier (platform prefix is optional, e.g., telegram_123 or 123 both work) token1, token2, ...: Token numbers to monitor Example: python3 skills/mrc-monitor/scripts/monitor.py telegram telegram_6046286675 73 97 42 # or python3 skills/mrc-monitor/scripts/monitor.py telegram 6046286675 73 97 42
Background Execution
Start the monitor as a background process so the agent responds immediately: import subprocess # channel_id can be with or without platform prefix (both work) cmd = ['python3', 'skills/mrc-monitor/scripts/monitor.py', platform, channel_id] + [str(t) for t in tokens] subprocess.Popen(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
Agent Response
After starting the monitor, respond immediately with: β Monitoring tokens: 73, 97, 42 Checking every 15 seconds. I'll notify you here when they're ready! π
One-Time Check
For "check 73" commands, perform a single Firebase query and respond with status without starting a background monitor.
Monitor Behavior
The monitor script: Polls Firebase Firestore every 15 seconds Checks all monitored tokens in each poll Sends "π Order X is ready!" notification when a token's status is "Ready" Removes notified tokens from the watch list Exits automatically when all tokens are notified Handles errors gracefully with retries Logs all activity to skills/mrc-monitor/logs/monitor_YYYYMMDD_HHMMSS.log
Error Handling
The script automatically handles: Network timeouts (retries up to 5 times) HTTP errors (including rate limits) Unexpected errors (stops after 5 consecutive failures) Signal termination (SIGTERM, SIGINT) On fatal errors, the script sends a notification before exiting.
Firebase Details
Project: kanteen-mrc-blr-24cfa Collection: orders Document fields: studentId (string): "student-{token_number}" status (string): "Preparing", "Ready", "Completed"
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Scripts
- SKILL.md
- scripts/monitor.py