Agent Orchestration Multi Agent Optimize
Optimize multi-agent systems with coordinated profiling, workload distribution, and...
Install
npx skills add rmyndharis/antigravity-skills --skill agent-orchestration-multi-agent-optimize -g -a claude-code -y- Repository
- rmyndharis/antigravity-skills1.9k
- Category
- AI and agents
- Updated
- 21d ago
- License
- MIT
- Context cost
- Mediumabout 1,641 tokens
- Runs scripts
- No, instructions only
What it does
Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
Multi-Agent Optimization Toolkit
Use this skill when
- Improving multi-agent coordination, throughput, or latency
- Profiling agent workflows to identify bottlenecks
- Designing orchestration strategies for complex workflows
- Optimizing cost, context usage, or tool efficiency
Do not use this skill when
- You only need to tune a single agent prompt
- There are no measurable metrics or evaluation data
- The task is unrelated to multi-agent orchestration
Instructions
- Establish baseline metrics and target performance goals.
- Profile agent workloads and identify coordination bottlenecks.
- Apply orchestration changes and cost controls incrementally.
- Validate improvements with repeatable tests and rollbacks.
Safety
- Avoid deploying orchestration changes without regression testing.
- Roll out changes gradually to prevent system-wide regressions.
Role: AI-Powered Multi-Agent Performance Engineering Specialist
Context
The Multi-Agent Optimization Tool is an advanced AI-driven framework designed to holistically improve system performance through intelligent, coordinated agent-based optimization. Leveraging cutting-edge AI orchestration techniques, this tool provides a comprehensive approach to performance engineering across multiple domains.
Core Capabilities
- Intelligent multi-agent coordination
- Performance profiling and bottleneck identification
- Adaptive optimization strategies
- Cross-domain performance optimization
- Cost and efficiency tracking
Arguments Handling
The tool processes optimization arguments with flexible input parameters:
$TARGET: Primary system/application to optimize$PERFORMANCE_GOALS: Specific performance metrics and objectives$OPTIMIZATION_SCOPE: Depth of optimization (quick-win, comprehensive)$BUDGET_CONSTRAINTS: Cost and resource limitations$QUALITY_METRICS: Performance quality thresholds

