aiwg Prompt模板 是 AI Skill Hub 本期精选AI工具之一。综合评分 8.0 分,整体质量较高。我们强烈推荐将其纳入你的 AI 工具库,帮助提升工作效率。
aiwg Prompt模板 是一款基于 TypeScript 开发的开源工具,专注于 多智能体、Prompt模板、自主编程 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
aiwg Prompt模板 是一款基于 TypeScript 开发的开源工具,专注于 多智能体、Prompt模板、自主编程 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
# 方式一:npm 全局安装 npm install -g aiwg # 方式二:npx 直接运行(无需安装) npx aiwg --help # 方式三:项目依赖安装 npm install aiwg # 方式四:从源码运行 git clone https://github.com/jmagly/aiwg cd aiwg npm install npm start
# 命令行使用
aiwg --help
# 基本用法
aiwg [options] <input>
# Node.js 代码中使用
const aiwg = require('aiwg');
const result = await aiwg.run(options);
console.log(result);
# aiwg 配置说明 # 查看配置选项 aiwg --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 AIWG_CONFIG="/path/to/config.yml"
<a href="https://aiwg.io"><img src="docs/.public/aiwg-readme-hero-v2.png" alt="AIWG — multi-agent AI framework, one source of truth; network connecting AI tools" width="1000"></a>
- Specialist agents — roles for architecture, implementation, testing, security, cloud, data engineering, research, content, and operations. - Workflow skills and commands — discoverable procedures for reviews, intake, research, curation, planning, and delivery. - Rules and review criteria — instructions for preserving work, handling sensitive configuration, checking claims, and reporting verification. - Artifact templates — structured requirements, design decisions, campaign briefs, source notes, runbooks, and review reports. - Multi-provider deployment — Google Antigravity CLI, Claude Code, OpenAI Codex, GitHub Copilot, Cursor, DeepSeek Harness, Factory AI, Hermes, OpenCode, OpenClaw, OpenHuman, Pi Coding Agent, Oh My Pi, Warp Terminal, and Devin Desktop. - Domain frameworks — software development, forensics, marketing, research, media curation, operations, knowledge base, and security engineering. - Dataset workflows — assessment, indexing, lineage, synchronization, and retirement through dataset intelligence; the separate aiwg-training project covers training-data curation and exports. - Memory addons — compound memory, line memory, wiki-oriented knowledge, and artifact lookup for different persistence needs. - Writing and voice tools — reusable voice profiles, context-sensitive diagnostics, revision workflows, and alternatives for content generation. - Testing quality — test conformance, reversible normalization, mutation testing, and flaky-test review. See the AIWG test conformance example for reviewed source controls and runner evidence. - Agent loops — bounded execution, failure analysis, checkpoints, and supported process recovery. - RLM — recursive context decomposition for tasks whose source material needs to be divided into smaller working sets. - YAML metalanguage — structured workflow and artifact definitions with schema-oriented validation. - MCP integration — tools and resources exposed through configured servers and provider connections. - Traceability and provenance — relationships between requirements, code, tests, sources, and generated artifacts. - Session history and diagnostics — import and inspect prior AI work, check deployment health, and diagnose provider wiring. - Project-local extensions and marketplace delivery — keep custom instructions with the project and package reusable capabilities through the appropriate distribution path.
The framework and addon catalog below describes these capabilities in more detail. Compatibility and execution requirements are explicit in the provider inventory and CLI reference.
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AIWG's workflow source is readable and editable. The main building blocks are:
- Agents — specialist role instructions, such as Security Auditor or Test Architect, with defined responsibilities and supported tool access. - Skills — reusable procedures an agent can find from a goal and follow during a task. - Commands — explicit ways to request a workflow through the provider or CLI. - Rules — constraints for the assistant to follow, with tool-based checks where configured. - Behaviors — lifecycle actions and hooks on providers that support them. - Templates — structures for requirements, briefs, review reports, runbooks, and other outputs.
Many assets use Markdown with YAML metadata; hooks and utilities may also include executable scripts or structured configuration. The provider determines how each asset is loaded or invoked. A role definition is not a separate model, and a written rule is not proof that its constraint was enforced.
The prompt-led installer at the top of this README is the canonical beginner path. For manual setup:
npm i -g aiwg
cd /path/to/your/project
aiwg use all --provider claude # replace claude with your provider selector
Deployment refreshes the shared context and reports verification and any required reload. Follow that result, then ask the agent to check the intended project and its AIWG connection. The manual installation reference covers the terminal path in detail.
For a deliberately narrower deployment, choose the relevant framework or addon instead of all. These are alternatives, not a sequence of required setup steps:
aiwg use sdlc --provider claude # Software development
aiwg use forensics --provider claude # Investigation workflows
aiwg use marketing --provider claude # Campaign and content work
aiwg use media-curator --provider claude # Media collections
aiwg use research --provider claude # Research artifacts
aiwg use civic-action --provider claude # Civic review and preparation
aiwg use rlm --provider claude # Context decomposition
For maintenance or an existing workspace that needs context migration, preview the relevant regeneration branch rather than treating every branch as installation:
Preview how to refresh this workspace’s provider context. If it needs existing-project extraction or migration, explain the proposed changes, preserve project-specific instructions, and verify the result.
The regeneration guide also covers canonical refresh and legacy compatibility. Use the branch that matches the workspace state. To scaffold a new project rather than connect the current one, see the new-project guide.
aiwg use all --provider antigravity # Google Antigravity CLI (alias: agy)
aiwg use all --provider claude # Claude Code
aiwg use all --provider codex # OpenAI Codex
aiwg use all --provider copilot # GitHub Copilot
aiwg use all --provider cursor # Cursor
aiwg use all --provider factory # Factory AI
aiwg use all --provider opencode # OpenCode
aiwg use all --provider warp # Warp Terminal
aiwg use all --provider devin # Devin Desktop
aiwg use all --provider openclaw # OpenClaw
aiwg use all --provider hermes # Hermes
aiwg use all --provider openhuman # OpenHuman
aiwg use all --provider pi # Pi Coding Agent
aiwg use all --provider omp # Oh My Pi
all means the complete deployable end-user surface. It intentionally omits contributor-only development bundles and packages that cannot be deployed directly.
Prerequisites: Node.js >=20.0.0 and an AI platform (Claude Code, GitHub Copilot, Cursor, Warp Terminal, or others). New installs should prefer Node 24. See Prerequisites Guide for details.
Release verification: Inspect the provenance and signature material for the release you install. The verification guide describes the available artifacts and commands.
The base global install intentionally excludes native packages whose lifecycle scripts require explicit trust. Core deployment, discovery, and provider tooling work without them. Enable only the capability you need:
Enable the native features needed for interactive terminals, semantic search, or graph-backed artifacts in this workspace. Explain which dependencies are required, install only the selected features, and verify they load.
The feature installer writes a private manifest and lockfile under the AIWG user data directory and approves scripts only for that feature. Do not set a broad user-level npm allow-scripts policy. If an older install left native package files present but unbuilt, aiwg doctor reports the broken capability and the same scoped rebuild command.
aiwg use supports project deployments, additive user mirrors, and a user-global bootstrap:
- Project scope — default. Run aiwg use all --provider <provider> from a project root and the artifacts land in that provider's project paths. This keeps project-specific instructions associated with the intended repository. Some providers also use user-level surfaces; check the reported deployment scope. This is the recommended default for new users. - User scope (additive mirror) — aiwg use all --provider <provider> --scope user keeps the project deployment and mirrors it to ~/.claude/agents/, ~/.claude/skills/, etc. - Global bootstrap — aiwg use all --provider claude --global installs framework and kernel assets in native user-level paths while leaving only lightweight context and provider bootstrap files in the current project. Ask the assistant to connect additional projects without deploying their own skill copies.
Shared user-level instructions can be useful for personal conventions, while project-local instructions keep a team's requirements and decisions with its repository. Review both scopes when a provider uses them together. The installer and provider inventory describe where files will go, so you can distinguish instructions that follow you across projects from instructions intended for this workspace.
See the Agentic Install Runbook for the zero-to-running setup path, and the CLI reference (under aiwg use → "Scope models") for the per-provider details and the global-install rough-edge inventory.
Add the AIWG marketplace to Claude Code and install the SDLC, Agent Loop, and Compound Memory plugins.
The marketplace contains independently packaged framework and addon plugins, so you can install only the capabilities a Claude Code workspace needs. Source-distributed opt-in addons such as Civic Action deploy with aiwg use civic-action and do not imply a marketplace wrapper.
aiwg 是一个基于 AI 驱动的软件开发生命周期(SDLC)加速工具。通过集成 GitHub,它能够根据描述自动生成并执行复杂的开发任务,旨在通过 AI 能力提升代码审查、架构设计及自动化流程的效率,让开发者从繁琐的重复劳动中解脱出来。
aiwg 拥有强大的 AI 能力矩阵,包含 188 个涵盖测试、安全、架构、DevOps、云原生、前后端及数据工程等领域的专业 Agents;提供 50 个 CLI 命令用于框架部署、项目脚手架搭建及指标验证;并内置 128 种 Workflow Skills,支持通过自然语言触发回归测试、取证分析及质量保障等自动化工作流。
aiwg 由五种基础原语构建:Agents(具备特定工具集的专业角色)、Skills(通过自然语言触发的自动化工作流)、Commands(显式斜杠命令)、Rules(会话强制执行指令)以及 Behaviors。用户可以通过 npm 进行全局安装:执行 `npm install -g aiwg` 即可快速完成部署。
在使用前,请确保环境已安装 Node.js >=20.0.0(推荐使用 Node 24),并配置好支持 MCP 协议的 AI 平台,如 Claude Code、GitHub Copilot、Cursor 或 Warp Terminal。对于 v2026.5.3+ 版本,所有发布版本均经过 Sigstore 签名与验证,确保了供应链的安全可靠。
aiwg 支持通过 MCP(Model Context Protocol)协议进行扩展。其 MCP server 可以将 AIWG 的产物管理、工作流执行及项目健康检查能力转化为工具,供任何兼容 MCP 的 AI 平台通过程序化方式调用,实现深度定制化配置。
aiwg 核心由六大组件构成,支持“双轨迭代模型”。例如使用 `aiwg sdlc-accelerate` 命令可以自动生成需求文档、架构基线、风险登记册及测试策略,并在每个阶段设置人工审批环节(Human Approval Gates),确保 AI 生成的内容符合预期并安全落地。
如果在执行 `npm i -g aiwg` 后提示找不到 `aiwg` 命令,通常是因为 npm 的全局 bin 目录未添加到系统的 PATH 环境变量中。你可以通过 `npm config get prefix` 获取全局路径,并使用 `export PATH="$(npm config get prefix)/bin:$PATH"` 将其添加到你的 shell 配置文件(如 .zshrc)中。
设计完整的多智能体认知架构,提供可复用Prompt模板,适合企业级自动化开发。代码质量优秀,社区关注度适中,值得推荐。
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。
✅ 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。
经综合评估,aiwg Prompt模板 在AI工具赛道中表现稳健,质量优秀。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。
| 原始名称 | aiwg |
| 原始描述 | 开源Prompt模板:Cognitive architecture for AI-augmented software development. Specialized agents。⭐133 · TypeScript |
| Topics | 多智能体Prompt模板自主编程Claude工作流自动化 |
| GitHub | https://github.com/jmagly/aiwg |
| License | MIT |
| 语言 | TypeScript |
收录时间:2026-05-18 · 更新时间:2026-05-19 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。