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Smart Auto Updater

Smart auto-updater with AI-powered impact assessment. Checks updates, analyzes changes, evaluates system impact, and decides whether to auto-update or just report. Perfect for hands-off maintenance with safety guarantees.

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High Signal

Smart auto-updater with AI-powered impact assessment. Checks updates, analyzes changes, evaluates system impact, and decides whether to auto-update or just report. Perfect for hands-off maintenance with safety guarantees.

โฌ‡ 0 downloads โ˜… 0 stars Unverified but indexed

Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
SKILL.md, _meta.json, references/integration.md, references/report-templates.md, references/risk-assessment.md

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.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. 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

Documentation

ClawHub primary doc Primary doc: SKILL.md 16 sections Open source page

Smart Auto-Updater

AI-powered auto-updater that intelligently decides whether to update based on impact assessment. Safe, intelligent, and configurable.

1. Check Phase

Checks for OpenClaw updates Checks for skill updates via ClawHub Fetches changelog and diff

2. AI Analysis Phase

Analyzes changes using LLM Evaluates system impact (ๆžถๆž„/ๆ€ง่ƒฝ/ๅ…ผๅฎนๆ€ง) Classifies risk level (HIGH/MEDIUM/LOW)

3. Decision Phase

Risk LevelActionHIGHSkip update, send detailed reportMEDIUMSkip update, send warning + reportLOWAuto-update, send summary

4. Report Phase

Generates readable update report Includes risk assessment Provides upgrade recommendations

Basic usage

# Run smart update check openclaw sessions spawn \ --agentId smart-auto-updater \ --message "Run smart update check"

With custom parameters

openclaw sessions spawn \ --agentId smart-auto-updater \ --message "Check updates with custom settings: auto-update LOW risk, report MEDIUM risk"

Environment Variables

# AI Model (optional, defaults to configured model) export SMART_UPDATER_MODEL="minimax-portal/MiniMax-M2.1" # Auto-update threshold (default: LOW) # Options: NONE (report only), LOW, MEDIUM export SMART_UPDATER_AUTO_UPDATE="LOW" # Risk tolerance (default: MEDIUM) # HIGH: Only auto-update LOW risk # MEDIUM: Auto-update LOW + MEDIUM risk # LOW: Auto-update all export SMART_UPDATER_RISK_TOLERANCE="MEDIUM" # Report level (default: detailed) # Options: brief, detailed, full export SMART_UPDATER_REPORT_LEVEL="detailed"

High Risk Report

  • ๐Ÿ”ด Smart Auto-Updater Report
  • Update Available: v1.2.3 โ†’ v1.3.0
  • โš ๏ธ Risk Level: HIGH
  • ๐Ÿ“‹ Changes Summary:
  • Breaking API changes detected
  • Database migration required
  • 3 files modified
  • ๐Ÿ—๏ธ Impact Assessment:
  • Architecture: MAJOR changes to core components
  • Performance: Potential impact on startup time
  • Compatibility: Breaks backward compatibility
  • ๐Ÿšซ Decision: SKIPPED
  • ๐Ÿ’ก Recommendations:
  • 1. Review changelog manually
  • 2. Test in staging environment
  • 3. Schedule maintenance window
  • ๐Ÿ—“๏ธ Next Check: 24 hours

Low Risk Auto-Update

  • ๐ŸŸข Smart Auto-Updater Report
  • Updated: v1.2.3 โ†’ v1.2.4
  • โœ… Risk Level: LOW
  • ๐Ÿ“‹ Changes:
  • Bug fixes (2)
  • Performance improvements (1)
  • ๐Ÿ—๏ธ Impact Assessment:
  • Architecture: No changes
  • Performance: Minor improvement
  • Compatibility: Fully compatible
  • โœ… Decision: AUTO-UPDATED
  • ๐Ÿ“Š Summary:
  • OpenClaw: v1.2.3 โ†’ v1.2.4
  • Skills updated: 2
  • Skills unchanged: 15
  • Errors: none
  • โฑ๏ธ Next Check: 24 hours

Architecture

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ Trigger (Cron) โ”‚ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ โ–ผ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ Check Updates โ”‚ โ† clawhub update --dry-run โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ โ–ผ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ AI Analysis โ”‚ โ† Analyze changes, assess risk โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ โ”Œโ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ” โ”‚ โ”‚ โ–ผ โ–ผ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ HIGH โ”‚ โ”‚ MEDIUMโ”‚ โ”‚ Skip โ”‚ โ”‚ Skip โ”‚ โ””โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”˜ โ”‚ โ”‚ โ–ผ โ–ผ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ LOW โ”‚ โ”‚ Reportโ”‚ โ”‚ Updateโ”‚ โ”‚ Only โ”‚ โ””โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”˜ โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ โ”‚ โ””โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚ โ–ผ โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚ Generate Report โ”‚ โ† Send summary โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

Safety Features

Dry Run First - Always check before acting Risk Classification - AI-powered impact assessment Configurable Thresholds - Set your own risk tolerance Detailed Logging - Every decision is logged Manual Override - Always can review before updating

Updates keep being skipped

Check risk tolerance setting Verify AI model is available Review changelog manually

False positives (too many HIGH risk)

Lower risk tolerance Check AI model prompts Review specific change patterns

Reports not being delivered

Verify delivery channel configuration Check gateway status Review session configuration

References

references/risk-assessment.md โ†’ AI risk assessment methodology references/report-templates.md โ†’ Report format examples references/integration.md โ†’ Integration with cron/jobs

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
4 Docs1 Config
  • SKILL.md Primary doc
  • references/integration.md Docs
  • references/report-templates.md Docs
  • references/risk-assessment.md Docs
  • _meta.json Config