An expert AI skill designed to achieve peak database performance through advanced query optimization, index strategies, and system-level tuning.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ah-database-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 ah-database-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 Database Optimizer?
The Database Optimizer is a high-performance Openclaw Skills module designed for developers and DBAs who need to eliminate bottlenecks and scale their data layer. It acts as a senior database tuning expert capable of analyzing complex execution plans and implementing sub-second query optimizations across various environments including PostgreSQL, MySQL, MongoDB, and more.
By focusing on resource utilization and system stability, this skill ensures your database architecture can handle increased traffic while reducing infrastructure costs. It provides deep technical insights into memory allocation, I/O patterns, and replication lag to maintain a robust and responsive data ecosystem.
Database Optimizer Use Cases
- Reducing P95 query latency from seconds to milliseconds in production environments.
- Designing high-efficiency indexing strategies to eliminate full table scans.
- Resolving database lock contention and deadlock issues in high-concurrency systems.
- Tuning memory parameters like buffer pools and cache hit rates for optimal throughput.
- Scaling database infrastructure through partitioning, sharding, and read replica routing.
How Database Optimizer Works
- Context Assessment: The skill initializes by querying the current database architecture and specific performance requirements.
- Analysis & Baseline: It reviews slow query logs, execution plans, and system metrics to identify the primary bottlenecks.
- Optimization Planning: The agent analyzes wait events, I/O patterns, and CPU utilization to formulate an improvement strategy.
- Implementation: It executes query rewrites, index creation, and configuration adjustments following a measure-first approach.
- Validation & Monitoring: The skill verifies that targets (e.g., <100ms query time, >90% cache hit rate) are met and provides a detailed impact report.
Database Optimizer Setup
To integrate this performance-focused module into your workflow, ensure your AI agent is configured to access your database schema or slow query logs. Install the skill via the Openclaw Skills manager:
openclaw install database-optimizer
Configure your environment variables for the specific database system you are tuning (e.g., PGHOST, MYSQL_PORT) to allow the optimizer to analyze execution plans directly.
Database Optimizer Data Schema & Taxonomy
The Database Optimizer organizes its analysis and outputs using a systematic taxonomy to ensure clarity and auditability:
| Data Category | Details Managed |
|---|---|
| Metrics | Query latency (P50/P95), cache hit ratios, lock wait times, and bloat percentages. |
| Plans | Detailed breakdowns of EXPLAIN ANALYZE output and node-level costs. |
| Schema Metadata | Table definitions, data type selections, and existing index structures. |
| Optimization Logs | A record of applied query rewrites, new index DDL, and configuration changes. |
Database Optimizer Advanced Features
- Multi-Engine Support: Specialized tuning profiles for PostgreSQL, Redis, Cassandra, ClickHouse, and Oracle.
- Cross-Agent Collaboration: Seamlessly works with Openclaw Skills like backend-developer and devops-engineer to align code and infrastructure.
- Automated Partition Pruning: Advanced logic for optimizing large-scale datasets through intelligent partitioning and archive policies.
- Wait Event Analysis: Granular troubleshooting of kernel-level bottlenecks and network latency issues.
- Replication Tuning: Optimization of parallel workers and network settings to minimize replication lag.
SKILL.md
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