Инструменты

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.

Business analytics plugin from the wshobson/agents marketplace: KPI dashboard design and data storytelling skills plus a business analyst subagent to choose metrics, plan dashboard layouts and turn data into reports executives or investors understand. Methods and templates only; no data connections.

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.

OpenAI's official Codex plugin with about 50 skills that route questions to genetics, omics, pathway, protein structure, chemistry and clinical evidence sources, can split the work across parallel subagents, and synthesize sourced conclusions.

Econometrician Pedro Sant'Anna's academic Claude Code setup (fork the repo to use it): Beamer/Quarto lecture slides, paper review and mock refereeing, R/Python analysis and replication packages, with specialist subagents and quality gates. Needs Git and Python; slides need XeLaTeX and Quarto.

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.