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A complete development methodology for coding agents: brainstorm to clarify requirements, write an implementation plan, then build with subagents, with red-green TDD, systematic debugging and code review throughout. In the official Claude Code and Codex marketplaces.

Self-improving agent from Nous Research with built-in memory and a learning loop that turns experience into skills. Works with any model provider; the hermes command has a terminal UI, and a gateway connects it to Telegram, Slack and more and runs scheduled tasks.

Toolkit for building Claude Code plugins: 7 skills on plugin structure, hooks, MCP integration, commands, subagents and skill writing, a guided eight-phase create command, and subagents for agent generation, plugin validation and skill review. Maintained by Anthropic.

Multi-agent orchestration framework for Claude Code and Codex, formerly Claude Flow: swarm coordination, self-learning memory and cross-machine federated communication. The marketplace offers 30+ plugins; full features need npx ruflo init.

Multi-agent orchestration framework formerly called Claude Flow: ruflo init gives Claude Code nearly 100 specialized subagents, swarm coordination, cross-session vector memory and hooks; add --codex to configure Codex instead. Also works as a standalone MCP server or plugin marketplace.

MLOps plugin from the wshobson/agents marketplace: data scientist, ML engineer and MLOps engineer subagents and a /ml-pipeline command that runs the pipeline in phases from data analysis and training to deployment and monitoring, plus ML pipeline and recommender system skills.

UI/UX design plugin from the wshobson/agents marketplace with 3 subagents, 9 skills and commands for design review, component creation and accessibility audits, covering design tokens, WCAG 2.2, responsive layout, iOS HIG and Material Design 3 for in-code UI design and review.

Quant trading plugin from the wshobson/agents marketplace: quant analyst and risk manager subagents plus backtesting and risk metrics skills for strategy backtests, portfolio optimization and risk measures like VaR, Sharpe ratio and max drawdown. Needs local Python; not investment advice.

Say build a harness for this project and it designs a domain-specific agent team, generating subagent definitions, companion skills and orchestration, validates them and keeps evolving them from feedback. Supports workflow orchestration, persistent agent teams and subagent delegation.

A research plugin for Claude Code: commands like /omp:survey, /omp:experiment and /omp:write chain literature review, topic selection, experiments, writing and self-review, with 5 specialized agents and 34 research skills that remember project progress across sessions. Experiments lean toward ML.