# Tools

> Every listed resource, editors’ picks first. The filters below can be combined.

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Resources for QA or ML / AI or Data analysis, Tagged `subagents`: 17 items.

> - QA: Functional testing, test automation and quality assurance.
> - ML / AI: Model training, evaluation and LLM application development.
> - Data analysis: Querying, statistical analysis, reporting and visualization.

- [Code Review](https://hebbmind.com/plugin/code-review.md): [Plugin] Reviews pull requests with several parallel subagents, scores each finding by confidence to filter out false positives, and can post the results as PR comments. Official Anthropic plugin; requires a logged-in GitHub CLI.
- [Hermes Agent](https://hebbmind.com/cli/hermes-agent.md): [CLI] 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.
- [PR Review Toolkit](https://hebbmind.com/plugin/pr-review-toolkit.md): [Plugin] Six specialized review subagents that check comment accuracy, test coverage, silent failures, type design, code style and simplification opportunities. Run them individually or all at once. Official Anthropic plugin.
- [Plugin Dev](https://hebbmind.com/plugin/plugin-dev.md): [Plugin] 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.
- [Ruflo](https://hebbmind.com/plugin/ruflo.md): [Plugin] 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.
- [Ruflo](https://hebbmind.com/cli/ruflo.md): [CLI] 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.
- [Accessibility Compliance](https://hebbmind.com/plugin/accessibility-compliance.md): [Plugin] Accessibility review plugin with an audit command, a UI validation subagent, and WCAG 2.2 and screen reader testing skills. Before design reviews or launch, the agent checks contrast, keyboard use and screen reader support and suggests fixes. For Claude Code; automated checks need Node.js.
- [Quantitative Trading](https://hebbmind.com/plugin/quantitative-trading.md): [Plugin] 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.
- [Business Analytics](https://hebbmind.com/plugin/business-analytics.md): [Plugin] 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.
- [Machine Learning Ops](https://hebbmind.com/plugin/machine-learning-ops.md): [Plugin] 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.
- [Agent Teams](https://hebbmind.com/plugin/agent-teams.md): [Plugin] Orchestrates multi-agent teams using Claude Code's experimental Agent Teams feature: parallel multi-angle code review, competing-hypothesis debugging and feature work split by file ownership. Enable CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS first.
- [TDD Workflows](https://hebbmind.com/plugin/tdd-workflows.md): [Plugin] Test-driven development plugin: /tdd-workflows:tdd-cycle and related commands move through red-green-refactor phases with a checkpoint for approval at each, plus TDD orchestrator and code reviewer subagents. Part of the wshobson/agents marketplace.
- [Awesome Claude Code Subagents](https://hebbmind.com/plugin/awesome-claude-code-subagents.md): [Plugin] 160+ specialized Claude Code subagents, packaged as plugins in 10 categories such as core development, languages, infrastructure, testing and security, and data and AI, so you install only what you need.
- [Harness](https://hebbmind.com/plugin/harness.md): [Plugin] 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.
- [Life Science Research](https://hebbmind.com/plugin/life-science-research.md): [Plugin] 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.
- [My Claude Code Setup (claude-code-my-workflow)](https://hebbmind.com/skill/claude-code-my-workflow.md): [Skill] 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.
- [Oh My Paper](https://hebbmind.com/plugin/oh-my-paper.md): [Plugin] 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.
