能力标签
⚙️
Agent工作流

多模型AI辩论工具

基于 JavaScript · 无代码搭建完整 AI 自动化流程
英文名:llm-peer-review
⭐ 6 Stars 🍴 1 Forks 💻 JavaScript 📄 MIT 🏷 AI 7.0分
7.0AI 综合评分
AI辩论多模型代码审查工作流JavaScript
✦ AI Skill Hub 推荐

经 AI Skill Hub 精选评估,多模型AI辩论工具 获评「推荐使用」。这款Agent工作流在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 7.0 分,适合有一定技术背景的用户使用。

📚 深度解析
多模型AI辩论工具 是一套完整的 AI Agent 自动化工作流方案。随着 AI 能力的不断提升,基于 Agent 的自动化工作流正在成为提升个人和团队效率的核心方式。区别于传统的 RPA 自动化(模拟鼠标键盘操作),AI Agent 工作流通过理解任务意图、动态规划执行路径,能够处理更复杂的非结构化任务。

多模型AI辩论工具 工作流的设计遵循"最小配置,最大复用"原则:核心逻辑已经封装好,用户只需配置自己的 API Key 和业务参数即可快速上手。工作流内置错误处理和重试机制,在网络波动或 API 限速等情况下仍能稳定运行,适合作为生产环境的自动化基础设施。

在实际部署时,建议先在测试环境中运行 3-5 次,验证各个环节的输出结果符合预期,再部署到生产环境。AI Skill Hub 评分 7.0 分,是同类 Agent 工作流中的精选推荐。
📋 工具概览

多模型AI辩论工具 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。

GitHub Stars
⭐ 6
开发语言
JavaScript
支持平台
Windows / macOS / Linux
维护状态
轻量级项目,按需更新
开源协议
MIT
AI 综合评分
7.0 分
工具类型
Agent工作流
Forks
1
📖 中文文档
以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

多模型AI辩论工具 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。

📌 核心特色
  • 可视化 Agent 工作流编排,无需编写复杂代码
  • 支持多步骤自动化任务链,实现全流程无人值守
  • 与外部 API、数据库和第三方服务无缝集成
  • 内置错误处理与自动重试机制,保障稳定运行
  • 提供可复用的自动化模板,快速在同类场景部署
🎯 主要使用场景
  • 自动化日常重复性工作,将精力集中于创造性任务
  • 构建数据采集 → 处理 → 输出的完整自动化管线
  • 实现跨平台、跨系统的数据流转和业务协同
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:npm 全局安装
npm install -g llm-peer-review

# 方式二:npx 直接运行(无需安装)
npx llm-peer-review --help

# 方式三:项目依赖安装
npm install llm-peer-review

# 方式四:从源码运行
git clone https://github.com/mayankmankhand/llm-peer-review
cd llm-peer-review
npm install
npm start
📋 安装步骤说明
  1. 访问 GitHub 仓库获取工作流文件
  2. 在对应平台(Dify / Flowise / Make 等)中找到「导入工作流」功能
  3. 上传工作流文件
  4. 按照提示配置必要的环境变量和 API Key
  5. 运行测试确认流程正常后投入使用
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 命令行使用
llm-peer-review --help

# 基本用法
llm-peer-review [options] <input>

# Node.js 代码中使用
const llm_peer_review = require('llm-peer-review');

const result = await llm_peer_review.run(options);
console.log(result);
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
# llm-peer-review 配置说明
# 查看配置选项
llm-peer-review --config-example > config.yml

# 常见配置项
# output_dir: ./output
# log_level: info
# workers: 4

# 环境变量(覆盖配置文件)
export LLM_PEER_REVIEW_CONFIG="/path/to/config.yml"
📑 README 深度解析 真实文档 完整度 90/100 含工作流图 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

LLM Peer Review

AI peer review for your work. (Also: a structured workflow.)

<img src="docs/images/ask-gpt-summary.png" alt="ask-gpt summary showing agreed points, disagreed points, recommended actions, and key insights" width="700">

A real /ask-gpt debate output: Claude and ChatGPT argue across three rounds and hand you a structured verdict (what they agreed on, where they disagreed, and a prioritized action list). You approve what gets implemented.

This toolkit gives you slash commands for every step of a project: explore the problem, create a plan, build, review, then run a 3-round debate between Claude and ChatGPT (or Gemini). Works for product specs, research plans, competitive analysis, and code.

Inspired by Zevi Arnovitz's workflow on Lenny's Podcast. The key difference: Zevi manually copies feedback between models. This toolkit automates the entire debate loop with two commands (/ask-gpt and /ask-gemini).

This is the same consensus/divergence synthesis that Perplexity's Model Council produces and what Karpathy's LLM Council does for general Q&A, applied to a full project lifecycle with multi-round adversarial debate and an implementation workflow.

New to slash commands? A slash command is a shortcut you type into your AI editor's chat panel - it starts with / and tells the AI to run a specific workflow. The editors that support them are Claude Code (Anthropic's CLI plus editor panel for Claude) and Cursor (an AI-powered code editor built on VS Code). You'll need one of these installed; see SETUP.md if you're starting from scratch.

---

What's new since v4.3.3

Five releases land as one upgrade if you last installed v4.3.3:

  • v4.4.0 - Codebase map. /index now produces CODEBASE_MAP.md, a semantic map (module purposes, conventions, gotchas) consumed by /explore, /create-plan, and /pair-debug. Replaces the flat-tree INDEX.md from v3.4.
  • v4.4.1 - Richer review explanations. All /review-* skills now use a 4-field finding structure (What / Why it matters / Example / Suggested fix). Cosmetic-only findings are dropped instead of being bulked up.
  • v4.5.0 - Model default safety net. /ask-gpt and /ask-gemini auto-override outdated GPT_MODEL or GEMINI_MODEL values in .env.local. Setting an old default (e.g. gpt-5.4) gets you the current default (gpt-5.5) with a one-line warning.
  • v4.5.1 - Documentation audit. README repositioned for newcomers, "What's new" rollup added to CHANGELOG, deprecated-model warning explainer added to API-KEYS.md, broken anchors fixed. Doc-only release, no behavior change.
  • v4.6.0 - Debate hardening. Two-PR cut. (#101) Empty-body detection in /ask-gpt and /ask-gemini: silent failures (token cap exhausted by reasoning, refusals, safety blocks) now throw a descriptive error naming both cause and fix. Default token cap raised from 4096 to 32000 (overridable via GPT_MAX_TOKENS / GEMINI_MAX_TOKENS). Each debate invocation gets a session ID embedded in its /tmp paths so two parallel Cursor or Claude Code tabs cannot clobber each other's transcripts. (#103) /ask-gpt and /ask-gemini final summaries now use the same 4-field finding structure as /review (What / Why it matters / Example / Suggested fix), with 🚫/⚠️/💡 emojis and R-IDs end-to-end. Disagreed Points use 🤔 instead of ⚠️ to avoid colliding with Warn severity.

See the full upgrade summary in CHANGELOG.md, or re-run setup to pick up everything automatically.

---

Requirements

This toolkit runs on macOS, Linux, or WSL (Windows Subsystem for Linux). Windows users: install WSL first.

---

`/explore` - Understand before you build

Asks 3-4 focused questions about scope, success criteria, and constraints before any code is written. Has two modes: scoping (you have a concrete idea, pressure-test the scope) and vision (you're thinking big-picture, challenge the premise itself). It picks a mode by reading your input, then asks you to confirm. You can switch modes any time. Useful when you're not yet sure what you're actually building.

Full prompt: .claude/commands/explore.md

`/execute` - Build it, update the plan as you go

Walks through the plan step by step, updating status emojis and progress in real time. Spawns parallel agents for [parallel] steps, runs [sequential] steps in order. Stops on critical blockers (e.g. the plan assumed an API supports a feature it doesn't) instead of pushing through a broken plan.

Full prompt: .claude/commands/execute.md

Manual Setup (run the script yourself)

Prefer to run the setup script yourself? Pick the script that matches your shell:

Bash (WSL, macOS, Linux):

bash /path/to/llm-peer-review/scripts/setup/setup.sh /path/to/your-project

PowerShell (for setup only - see Requirements):

powershell -ExecutionPolicy Bypass -File C:\path\to\llm-peer-review\scripts\setup\setup.ps1 -Target "C:\path\to\your-project"

Or run from inside your project directory (no target needed):

cd /path/to/your-project
bash /path/to/llm-peer-review/scripts/setup/setup.sh

Note: If you run the script from inside the toolkit repository without specifying a target, it shows an error to prevent accidentally copying files into the wrong place.

What setup does: - Copies into your project: commands, skills, runtime scripts (ask-gpt.js, ask-gemini.js, browse.js), the index generator, VERSION, and .env.local.example. Detects and removes any legacy INDEX.md. The new CODEBASE_MAP.md (a semantic map of your project) is generated on your first /explore run, when Claude auto-invokes /index. - Preserves your work: CLAUDE.md, LESSONS.md, and settings.local.json are skipped if they already exist - those are yours to customize. - Always updates: toolkit rules (.claude/rules/toolkit.md). - Stays in the toolkit repo: setup scripts (setup.sh, setup.ps1, install-alias.*) are never copied.

See How It Works for details on which files are yours vs. managed by the toolkit.

One install covers everything - it stays inside .claude/scripts/ so your

For /review-browser, install the Chromium browser:

npx --prefix .claude/scripts playwright-core install chromium

On Linux/WSL, also: sudo npx playwright-core install-deps chromium

```

The debate commands and the browser command are optional. Skip the API keys if you don't want /ask-gpt and /ask-gemini. Skip the Chromium install if you don't want /review-browser. The core workflow commands work either way.

</details>

Never set up a dev environment before? Follow the step-by-step guide in SETUP.md. It covers Windows (WSL), Mac, Node.js, GitHub CLI, Cursor, and API keys - everything you need from scratch.
Not using Cursor? The setup guide assumes Cursor, but the toolkit works with any editor that supports Claude Code. Copy the relevant setup page into any AI assistant and ask it to rewrite the steps for your editor.

---

Install the toolkit's runtime packages (one-time, stays in .claude/scripts/).

npm install --prefix .claude/scripts

Example

You: /ask-gpt

Claude: What would you like me to review?
        1. Plan    2. Code    3. Branch    4. Feature    5. Other

You: Review the auth middleware

Claude: [Gathers context → sends to ChatGPT → they debate 3 rounds]

        --- Summary ---
        Agreed: Add token expiry check, extract magic numbers

        Recommended Actions:
        - [ ] Add token expiry validation
        - [ ] Move 3600 to TOKEN_EXPIRY_SECONDS

        Want me to implement these?

You: Yes

Want a different perspective? Run /ask-gemini next.

API costs: Each 3-round debate typically costs $0.01-$0.10 in API credits depending on context size. You'll need an OpenAI and/or Gemini API key with credits. See API-KEYS.md for a step-by-step setup guide.

Choosing what to review:

<img src="docs/images/ask-gpt-prompt.png" alt="ask-gpt prompt showing review options" width="700">

---

Open .env.local and paste your API keys

Edit .env.local and paste your OPENAI_API_KEY and GEMINI_API_KEY

For /ask-gpt and /ask-gemini, set up your API keys:

cp .env.local.example .env.local

AI debate commands (/ask-gpt, /ask-gemini): set up API keys

cp .env.local.example .env.local

The Workflow

flowchart TD W(["/worktree (optional)"]) -.-> A(["/explore"]) A --> B(["/create-plan"]) B --> C(["/execute"]) C --> D(["/review"]) D --> E(["/ask-gpt or /ask-gemini"]) E --> F(["Agreed · Disagreed · Actions"]) F --> G{"You approve"} G --> H(["/document"])
If the diagram doesn't render: /worktree (optional) -> /explore -> /create-plan -> /execute -> /review -> /ask-gpt or /ask-gemini -> /document

You don't have to use every command every time. Following the order prevents the most common mistake: coding before you've thought it through.

Want to see this in action? Follow the 5-minute walkthrough in DEMO-SCRIPT.md.
Working on multiple things at once? Use /worktree first to create an isolated copy, then open it in a new Cursor window and run /explore there.

---

project's own package.json is never touched.

npm install --prefix .claude/scripts

Browser QA (/review-browser): install Chromium

npx --prefix .claude/scripts playwright-core install chromium

Troubleshooting

  • Commands don't show up in Cursor - Make sure .claude/commands/ exists in your project root with .md files inside. The editor workspace root must be the folder that contains .claude/.
  • /ask-gpt or /ask-gemini fails - Check that npm install --prefix .claude/scripts was run and .env.local has valid API keys.
  • /ask-gpt or /ask-gemini prints a "deprecated model" warning - v4.5.0 auto-overrides outdated GPT_MODEL or GEMINI_MODEL env values with the current default. Edit .env.local to remove or update the stale value if you want to silence the warning. See API-KEYS.md.
  • "setup.sh: command not found" - Run the full command from the setup instructions, not just setup.sh on its own.
  • "target directory does not exist" - Create the project folder first: mkdir -p /path/to/project
  • Script errors with /bin/bash^M or "bad interpreter" - Line-ending issue. Your shell scripts have Windows-style line endings (CRLF) instead of Unix-style (LF). Easiest fix: delete the folder and clone fresh. Advanced fix: run git add --renormalize . && git checkout -- . in the repo.
  • I customized a toolkit file and upgraded - where did it go? - The setup script preserves your original at .toolkit-backup-<timestamp>/ at the project root before overwriting. Copy it back if you want to keep your version. Safe to delete the backup directory when done.
  • Setup one-liner fails partway through - Safe to rerun the command. Leftover /tmp/tmp.* folders are harmless and can be deleted. .toolkit-backup-*/ directories from prior runs are also safe to delete once you have confirmed you do not need the originals.
  • Commands seem outdated or missing sections - Delete any toolkit command files from ~/.claude/commands/. Global copies override project commands and cause stale behavior. The setup script warns about this automatically.

---

🎯 aiskill88 AI 点评 B 级 2026-05-24

创新的多模型对比评审框架,适合需要多角度论证的场景。但项目热度不高,文档生态待完善。

⚡ 核心功能
👥 适合人群
自动化工程师和运维人员项目经理和业务分析师希望减少重复性工作的专业人士数字化转型团队
🎯 使用场景
  • 自动化日常重复性工作,将精力集中于创造性任务
  • 构建数据采集 → 处理 → 输出的完整自动化管线
  • 实现跨平台、跨系统的数据流转和业务协同
⚖️ 优点与不足
✅ 优点
  • +MIT 协议,可免费商用
  • +大幅减少重复性人工操作
  • +可视化流程,清晰直观
  • +可扩展性强,支持复杂场景
⚠️ 不足
  • 初始配置和调试需投入一定时间
  • 强依赖外部服务的稳定性
  • 复杂场景需具备一定技术基础
⚠️ 使用须知

AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。

建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。

📄 License 说明

✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。

🔗 相关工具推荐
🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合
❓ 常见问题 FAQ
llm-peer-review 是一款JavaScript开发的AI辅助工具。开源AI工作流:Multi-model AI debate for your entire project lifecycle. Plans, specs, research,。⭐6 · JavaScript 主要应用场景包括:项目规划和决策、代码审查与优化、技术方案评审。
💡 AI Skill Hub 点评

AI Skill Hub 点评:多模型AI辩论工具 的核心功能完整,质量良好。对于自动化工程师和运维人员来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。

⬇️ 获取与下载
⬇ 下载源码 ZIP

✅ MIT 协议 · 可免费商用 · 直接从 aiskill88 服务器下载,无需跳转 GitHub

📚 深入学习 多模型AI辩论工具
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 llm-peer-review
原始描述 开源AI工作流:Multi-model AI debate for your entire project lifecycle. Plans, specs, research,。⭐6 · JavaScript
Topics AI辩论多模型代码审查工作流JavaScript
GitHub https://github.com/mayankmankhand/llm-peer-review
License MIT
语言 JavaScript
🔗 原始来源
🐙 GitHub 仓库  https://github.com/mayankmankhand/llm-peer-review

收录时间:2026-05-24 · 更新时间:2026-05-26 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。