optimize
Comprehensive performance optimization across database, backend, frontend, and infrastructure layers
Best use case
optimize is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Comprehensive performance optimization across database, backend, frontend, and infrastructure layers
Teams using optimize should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/optimize/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How optimize Compares
| Feature / Agent | optimize | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Comprehensive performance optimization across database, backend, frontend, and infrastructure layers
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Performance Optimization Skill You are routing performance optimization requests to specialized operations. Parse the `$ARGUMENTS` to determine which optimization operation to execute. ## Available Operations - **analyze** - Comprehensive performance analysis with bottleneck identification - **database** - Database query and schema optimization - **backend** - Backend API and algorithm optimization - **frontend** - Frontend bundle and rendering optimization - **infrastructure** - Infrastructure and deployment optimization - **benchmark** - Performance benchmarking and regression testing ## Routing Logic Extract the first word from `$ARGUMENTS` as the operation name, and pass the remainder as operation parameters. **Arguments received**: `$ARGUMENTS` **Base directory**: `/home/danie/projects/plugins/architect/open-plugins/plugins/10x-fullstack-engineer/commands/optimize/` **Routing Instructions**: 1. **Parse the operation**: Extract the first word from `$ARGUMENTS` 2. **Load operation instructions**: Read the corresponding operation file 3. **Execute with context**: Follow the operation's instructions with remaining parameters 4. **Invoke the agent**: Leverage the 10x-fullstack-engineer agent for optimization expertise ## Operation Routing ``` analyze → Read and follow: /home/danie/projects/plugins/architect/open-plugins/plugins/10x-fullstack-engineer/commands/optimize/analyze.md database → Read and follow: /home/danie/projects/plugins/architect/open-plugins/plugins/10x-fullstack-engineer/commands/optimize/database.md backend → Read and follow: /home/danie/projects/plugins/architect/open-plugins/plugins/10x-fullstack-engineer/commands/optimize/backend.md frontend → Read and follow: /home/danie/projects/plugins/architect/open-plugins/plugins/10x-fullstack-engineer/commands/optimize/frontend.md infrastructure → Read and follow: /home/danie/projects/plugins/architect/open-plugins/plugins/10x-fullstack-engineer/commands/optimize/infrastructure.md benchmark → Read and follow: /home/danie/projects/plugins/architect/open-plugins/plugins/10x-fullstack-engineer/commands/optimize/benchmark.md ``` ## Error Handling If no operation is specified or the operation is not recognized, display: **Available optimization operations**: - `/optimize analyze` - Comprehensive performance analysis - `/optimize database` - Database optimization - `/optimize backend` - Backend API optimization - `/optimize frontend` - Frontend bundle and rendering optimization - `/optimize infrastructure` - Infrastructure and deployment optimization - `/optimize benchmark` - Performance benchmarking **Example usage**: ``` /optimize analyze target:"user dashboard" scope:all metrics:"baseline" /optimize database target:queries context:"slow SELECT statements" threshold:500ms /optimize backend target:api endpoints:"/api/users,/api/products" load_profile:high /optimize frontend target:bundles pages:"dashboard,profile" metrics_target:"lighthouse>90" /optimize infrastructure target:scaling environment:production provider:aws /optimize benchmark type:load baseline:"v1.2.0" duration:300s concurrency:100 ``` **Comprehensive workflow example**: ```bash # 1. Analyze overall performance /optimize analyze target:"production app" scope:all metrics:"baseline" # 2. Optimize specific layers based on analysis /optimize database target:all context:"queries from analysis" threshold:200ms /optimize backend target:api endpoints:"/api/search" priority:high /optimize frontend target:all pages:"checkout,dashboard" framework:react # 3. Benchmark improvements /optimize benchmark type:all baseline:"pre-optimization" duration:600s # 4. Optimize infrastructure for efficiency /optimize infrastructure target:costs environment:production budget_constraint:true ``` ## Integration with 10x-Fullstack-Engineer All optimization operations should leverage the **10x-fullstack-engineer** agent for: - Expert performance analysis across all layers - Industry best practices for optimization - Trade-off analysis between performance and maintainability - Scalability considerations - Production-ready implementation guidance ## Execution Based on the parsed operation from `$ARGUMENTS`, read the appropriate operation file and follow its instructions with the remaining parameters.
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