agent-orchestration-multi-agent-optimize - Multi-Agent Optimization Toolkit
Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration.
Tags
Updated: 2026-09-17Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Profile agent workloads
- Identify performance bottlenecks
- Distribute agent workloads dynamically
- Compress context windows semantically
- Track LLM token costs
- Reduce inter-agent communication latency
Inputs
- Target system or application
- Performance metrics and objectives
- Optimization scope definition
- Cost and resource constraints
- Quality metric thresholds
Outputs
- Aggregated performance profile
- Compressed context data
- Performance tracking logs
- Optimal model selection decisions
Requirements
- Measurable performance metrics or evaluation data
- Python runtime environment
- LLM API access for target models