A built-in performance management suite for monitoring, analyzing, and automatically optimizing the execution of AI coding agent skills.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install yuyonghao-auto-optimizer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install yuyonghao-auto-optimizer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Auto Optimizer?
Auto Optimizer is an essential performance toolkit designed specifically for developers working within the Openclaw Skills framework. It serves as a comprehensive lifecycle management tool that monitors real-time execution data, identifies critical resource bottlenecks, and generates actionable optimization plans. By bridging the gap between performance monitoring and code improvement, it ensures that AI agents remain fast, reliable, and resource-efficient.
The tool addresses common development hurdles such as memory leaks, high execution latency, and unpredictable performance degradation. Through its modular architecture—consisting of a monitor, analyzer, engine, and applier—it provides a seamless workflow for maintaining high-quality code and optimal resource utilization in complex agentic environments.
Auto Optimizer Use Cases
- Real-time monitoring of execution duration and memory consumption for complex AI workflows.
- Automated detection of memory leaks and garbage collection pressure in long-running agent processes.
- Generating structured optimization strategies like LRU caching and batch processing to improve responsiveness.
- Proactive identification of performance regressions during the development lifecycle of Openclaw Skills.
How Auto Optimizer Works
- The PerformanceMonitor captures execution metrics, including duration and memory usage, for every operation.
- The BottleneckAnalyzer evaluates this historical data against predefined thresholds to detect code smells or resource issues.
- The OptimizationEngine creates a tailored plan containing specific recommendations like async conversion or error-handling enhancements.
- The OptimizationApplier executes the plan to modify the code automatically or performs a dry-run for developer review.
Auto Optimizer Setup
This performance tool is built directly into the core environment and does not require external package installation. To get started, simply import the required modules into your project.
# Skill is built-in; no additional installation steps required
Auto Optimizer Data Schema & Taxonomy
Auto Optimizer organizes performance data and optimization metadata into several structured categories for easy reporting and auditing.
| Category | Description | Data Format |
|---|---|---|
| Performance Metrics | Contains execution time, memory usage, and operation metadata | JSON |
| Bottleneck Analysis | Details detected issues, confidence scores, and rule IDs | JSON / Markdown |
| Optimization Plans | Lists recommended actions, strategies, and implementation paths | JSON / Markdown |
| Exported Reports | Summarized statistical analysis of skill performance over time | CSV / JSON |
Auto Optimizer Advanced Features
- Multi-skill analysis for managing performance across diverse Openclaw Skills simultaneously.
- Custom rule definitions for BottleneckAnalyzer to target domain-specific performance requirements.
- Automated rollback functionality to safely revert optimizations if performance does not meet expected targets.
- Dry-run mode for the OptimizationApplier to preview code changes without affecting the live codebase.
SKILL.md
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