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By EricGrill
Orchestrate multi-agent AI workflows by dynamically managing context with vector DBs, knowledge graphs, RAG, and memory systems, while optimizing agent performance through metrics analysis, profiling across database-app-frontend stacks, baseline reporting, and prompt engineering like chain-of-thought and few-shot examples.
npx claudepluginhub ericgrill/agents-skills-plugins --plugin agent-orchestrationSystematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
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.
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Uses Bash, Write, or Edit tools
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Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.
Advanced multi-agent coordination platform with task orchestration, performance monitoring, and workflow optimization. Features hooks for agent lifecycle events and MCP server for state management.
High-intelligence Claude Code copilot with deep code reasoning, evidence-driven planning, orchestration-first execution, model routing, context budgeting, CI/CD integration, enterprise security, plugin development, prompt engineering, performance profiling, agent teams, channels (event-driven autonomy with CI webhook, mobile approval relay, Discord bridge, and fakechat dev profile), interactive tutorials, LSP integration, security-hardened hook script library, MCP Prompts coverage, common workflow packs, runtime selection guide, computer-use patterns, checkpointing, scheduled-task blueprints, repo bootstrap scanner, hook policy engine (8 installable packs), layered memory deployment, role-based subagent packs (implementer, debugger, migration-lead, dependency-auditor, release-coordinator), 5 agent-team topology kits, autonomy operating mode (4 profiles + 3 gates), and a queryable 15-tool MCP documentation server with autonomy advisor.
Multi-agent orchestration with AI SDK v5 - handoffs, routing, and coordination for any AI provider (OpenAI, Anthropic, Google)
Multi-agent orchestrator — supervisor loop that launches agents to implement plans
Dynamic orchestrator plugin — 200+ agents, 200+ skills, hooks, and MCP servers. Upstream sources linked via git submodules (agency-agents, everything-claude-code, oh-my-claudecode, gstack, superpowers)
Automated code review for pull requests using multiple specialized agents with confidence-based scoring
Context management with save and restore capabilities
Customer support and sales automation agents
Team collaboration with DX optimization, issue tracking, and standup notes
LLM application development with RAG, embeddings, LangChain, and prompt engineering
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