By ahump20
Multi-agent system optimization, agent improvement workflows, and context management
Systematic 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.
Uses power tools
Uses Bash, Write, or Edit tools
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npx claudepluginhub ahump20/agents-skillz --plugin agent-orchestrationPre-deployment checks, configuration validation, and deployment readiness assessment
Team workflows, issue management, standup automation, and developer experience optimization
CI/CD pipeline configuration, GitHub Actions/GitLab CI workflow setup, and automated deployment pipeline orchestration
API testing automation, request mocking, OpenAPI documentation generation, observability setup, and monitoring
Unofficial cross-ecosystem skills marketplace. Context7-pattern MCP server that resolves, fetches, and installs skills from both Claude Code (anthropics/claude-plugins-official, anthropics/skills) and OpenAI Codex (openai/plugins, openai/skills, openai/codex-plugin-cc) — one registry, two clients. Not affiliated with Anthropic or OpenAI.
Harness-native ECC plugin for engineering teams - 67 agents, 278 skills, 94 legacy command shims, reusable hooks, rules, MCP conventions, and operator workflows for Claude Code plus adjacent agent harnesses
The Claude Code knowledge system — 380+ skills, 182+ agents, 100+ commands, 40 hooks, 32 rules, and workflows.
Comprehensive feature development workflow with specialized agents for codebase exploration, architecture design, and quality review
Comprehensive C4 architecture documentation workflow with bottom-up code analysis, component synthesis, container mapping, and context diagram generation
v9.52.0 - Reliability wave: tangle contextual review correction loop with hard round ceiling, progress-supervised review rounds (per-agent stall watch, descendant-tree kills), council diversity and agy pin fixes, marketplace generator source-of-truth fix, provider troubleshooting runbook and cost-expectations docs. Run /octo:setup.