能力标签
智能工作流
⚙️
Agent工作流

智能工作流

基于 TypeScript · 无代码搭建完整 AI 自动化流程
英文名:robrain
⭐ 61 Stars 🍴 4 Forks 💻 TypeScript 📄 NOASSERTION 🏷 AI 7.5分
7.5AI 综合评分
ai-agentstypescriptcontext-engineering
⚙️ 配置说明
✦ AI Skill Hub 推荐

智能工作流 是 AI Skill Hub 本期精选Agent工作流之一。综合评分 7.5 分,整体质量较高。我们推荐使用将其纳入你的 AI 工具库,帮助提升工作效率。

📚 深度解析

智能工作流 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。

智能工作流 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 7.5 分,是同类 Agent 工作流中的精选推荐。

📋 工具概览

智能工作流 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
⭐ 61
开发语言
TypeScript
支持平台
Windows / macOS / Linux
维护状态
轻量级项目,按需更新
开源协议
NOASSERTION
AI 综合评分
7.5 分
工具类型
Agent工作流
Forks
4

📖 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」。

智能工作流 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 robrain

# 方式二:npx 直接运行(无需安装)
npx robrain --help

# 方式三:项目依赖安装
npm install robrain

# 方式四:从源码运行
git clone https://github.com/adelinamart/robrain
cd robrain
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
robrain --help

# 基本用法
robrain [options] <input>

# Node.js 代码中使用
const robrain = require('robrain');

const result = await robrain.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
# robrain 配置说明
# 查看配置选项
robrain --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 ROBRAIN_CONFIG="/path/to/config.yml"
📑 README 深度解析 真实文档 完整度 57/100 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。

RoBrain

Stop watching your AI agent repeat the same mistakes.

Open-source shared memory for teams using AI agents. Captures every decision and the alternatives your team ruled out, and flags when a new decision contradicts an old one — so your team revisits past decisions intentionally, instead of re-litigating from zero.

Works across Claude Code, Cursor, and Copilot.

RoBrain is built by Rory Plans, an agent orchestration platform; it is the memory layer that keeps multi-agent, multi-developer work coherent over time.

Install and usage

You install one thing — the Sensing MCP — and run one Docker command. That's the whole setup.

Install details

pnpm docker:up brings up Postgres + Perception in the background; the user-facing surfaces are Sensing and the robrain CLI. npx robrain init-project writes the project instructions that tell Claude Code to call the Sensing tools at session start and end.

Self-hosted setup usually needs two keys: ANTHROPIC_API_KEY for extraction and one embedding-provider key for semantic retrieval. If that surprises you, see Why are there two API keys in self-hosted mode?.

#### Prerequisites - Docker + Docker Compose - Node.js 18.18+ (older 18.x + npm 9.6 can break npx bin permissions; upgrade Node or use pnpm dlx robrain), pnpm - Anthropic API key (for Haiku extraction) - OpenAI, Voyage, or Cohere API key (for embeddings)

Repo setup and .env

From the repository root:

git clone https://github.com/adelinamart/robrain
cd robrain
cp .env.example .env

Edit .env at the repo root (the same keys power Perception in Docker and the CLI install prompts). Paste real keys from Anthropic and your embedding provider — do not commit that file.

ANTHROPIC_API_KEY=
EMBEDDING_PROVIDER=openai
OPENAI_API_KEY=

Keep EMBEDDING_PROVIDER identical between this file and what you select when running install (or set EMBEDDING_PROVIDER in .env and install will pick it up without prompting).

What init-project writes

robrain init-project writes mode-aware instructions:

  • Free / self-hosted (robrain install --self-hosted): generated CLAUDE.md / Cursor rule uses only sensing_* tools.
  • Cloud / Control-enabled: generated instructions include both sensing_* and control_* calls.

CLI on your PATH (optional)

If you prefer not to use npx every time, install the package globally, then use the robrain command directly:

npm install -g robrain

Open a new terminal, or in zsh run rehash so your shell picks up the new binary. Then:

```bash robrain install --self-hosted

Stale Perception Docker image (migrations / schema out of sync)

If you pulled new code but did not rebuild the perception service, the container may still run an older Perception binary than packages/perception-self-hosted on disk. Then startup migrations (for example reviewed_at on decisions) never run, robrain review approval can fail against the DB the CLI is using, and features that assume the new schema break in confusing ways.

From the repo root (same directory as .env and docker/docker-compose.yml):

pnpm docker:up:build

That runs prepare-env and docker compose … up -d --build perception — rebuilds the Perception image and recreates the container.

To build only, then start Perception yourself:

pnpm docker:build
docker compose -f docker/docker-compose.yml --env-file .env up -d perception

If Docker reused layers and you still see old behavior, force a clean rebuild (no pnpm shortcut for --no-cache yet):

docker compose -f docker/docker-compose.yml --env-file .env build --no-cache perception
docker compose -f docker/docker-compose.yml --env-file .env up -d perception

Sanity check:

curl -sf "http://localhost:${PERCEPTION_PORT:-3001}/health"

After shared types change (packages/shared): downstream packages read @robrain/shared types from dist/. From repo root run pnpm --filter @robrain/shared build (or pnpm -r build) before relying on pnpm typecheck or publishing — otherwise packages/*/dist/*.d.ts can lag packages/shared/src.

Verify the running container matches your checkout: tail Perception logs while exercising capture — you should see current behavior (for example embedding dedupe logs as POST /signals deduped with matched decision text when a near-duplicate is skipped):

docker compose -f docker/docker-compose.yml logs -f --tail=80 perception

Note: A brand-new Postgres volume applies packages/shared/schema.sql on first boot. Existing volumes rely on Perception’s idempotent startup migrations when you run an up-to-date image — so after upgrading, rebuild and restart perception once.

---

Quick start — self-hosted

From a fresh clone, copy .env.example to .env, add your ANTHROPIC_API_KEY plus one embedding-provider key, then run:

pnpm install && pnpm build
pnpm docker:up
These first three commands run once from the robrain clone.

npm install -g robrain
npx robrain install --self-hosted --repo-root "$(pwd)"
These commands install the Robrain package and then set-up everything so Robrain can run.

cd /path/to/your/project && npx robrain init-project
The last command runs once per application repo.

Why are there two API keys in self-hosted mode?

RoBrain uses Anthropic (Haiku) for decision extraction/classification and a separate embeddings provider (openai, voyage, or cohere) for semantic vector search. That is why you may see both ANTHROPIC_API_KEY and an embedding key in setup.

Cheapest recommended combo: ANTHROPIC_API_KEY (Haiku) + EMBEDDING_PROVIDER=openai with OPENAI_API_KEY (text-embedding-3-small).

CLI commands

All commands accept --help for full flag details. Repo-level pnpm scripts live in package.json; CLI commands live in packages/cli.

CommandWhat it does
pnpm install:self-hostedBuild everything + run robrain install --self-hosted --repo-root . in one shot
pnpm buildCompile all workspace packages (pnpm -r build) — run after pnpm install in the robrain clone
pnpm docker:upStart Postgres + Perception (uses .env)
pnpm docker:up:buildSame, but force a rebuild of Perception
pnpm docker:buildRebuild Perception image without starting
pnpm docker:downStop the stack
pnpm synthesis:buildCompile @robrain/synthesis before running it
pnpm synthesis:dry-runRun Synthesis with SYNTHESIS_DRY_RUN=true (no DB writes)
npx robrain install --self-hostedWire Sensing MCP into Claude Code / Cursor; then runs **init-project in the current directory** by default
npx robrain install --token <token>Authenticate against Rory Plans cloud (or set RORY_TOKEN)
npx robrain install --editor <claude-code\|cursor\|copilot>Target a specific editor instead of all detected
npx robrain install --perception-url <url>Override Perception URL for self-hosted (default http://localhost:3001)
npx robrain install --repo-root <path>Path to the robrain clone — needed so MCP bundle gets linked (or set ROBRAIN_REPO)
npx robrain install --skip-init-projectWire editors only — do not run **init-project** in the current directory after install
npx robrain init-projectWarm-start memory from package.json, README, git log
npx robrain init-project --project-id <id>Override the auto-derived project ID (useful after projects merge)
npx robrain initAlias for init-project
npx robrain projects listList Perception projects with session/decision counts (recover phantom ids)
npx robrain projects merge <from-id> <to-id>Merge one project id into another in the database
npx robrain reviewInspect, edit, or delete captured decisions; conflict **“keep”** can persist a **related_to** edge when Perception returns a counterpart id so Synthesis stops re-flagging the pair
npx robrain review --session <id>Review a specific session (default: last session)
npx robrain review --allShow all active decisions, not only the last session
npx robrain review --limit <n>Max decisions to fetch (default: **20**)
npx robrain review --historyShow full decision lifecycle including superseded decisions
npx robrain review --approve-allBulk-approve every reviewable decision in the current fetch (no prompts per row)
npx robrain export-memoryExport approved decisions into Claude Code auto-memory files; optional **--cwd** / **--project-id** for non-interactive paths (Synthesis F2)
npx robrain export-memory --dry-runPreview the file plan without touching disk
npx robrain export-memory --include-unreviewedAlso export decisions not yet approved (not recommended)
npx robrain export-memory --to <dir>Write to a custom memory dir instead of ~/.claude/projects/<slug>/memory
npx robrain export-memory --ledgerAlso write a single git-committed decisions ledger (default: <project>/decisions.md); DB is source of truth — file is regenerated each run
npx robrain export-memory --ledger <path>Same as --ledger, but write to a custom path under the project root (e.g. docs/decisions.md)
npx robrain injectGet formatted context to paste into Claude Code
npx robrain inject --query "..."Semantic search for relevant decisions
npx robrain inject --files "..."Get decisions about specific files
npx robrain inject --copyCopy output directly to clipboard
npx robrain inject --allRequest up to **100** decisions (server cap): all **unreviewed** without --query, or a wider semantic pool with --query
npx robrain inject --limit <n>Cap how many decisions are returned (default: **5**)
npx robrain explain <file>Answer "why does this code exist?" for any file
npx robrain explain <file> --whyFull rationale + rejected alternatives per decision
npx robrain explain <file> --copyCopy explain output to the clipboard
npx robrain rule --add "..."Add a Planning rule (**Rory Plans cloud** — requires planningUrl in config)
npx robrain rule --listList rules from Planning **GET /facts** when cloud is configured; OSS-only prints guidance
npx robrain rule --remove <id>Remove a rule by id (cloud Planning API)
npx robrain rule --type <type>When using **--add**, set rule type: **always_include**, **always_exclude**, or **preference** (default: **preference**)
npx robrain statusAuth + Perception/Planning health + **active decision count** for the current project
npx robrain logoutClear locally stored credentials (Rory Plans token / install state)
pnpm synthesis:run**[Synthesis](#synthesis)** — batch job from **robrain repo root** (pnpm must resolve @robrain/synthesis)
npx robrain synthSame job via CLI: optional **--dry-run**, **--full**, **--lookback <n>**, **--project <id>**. Resolves the robrain monorepo from this CLI package unless **ROBRAIN_REPO** is set (needed for some global installs).

Or via Perception API (Authorization required)

curl -s -H "Authorization: Bearer <PERCEPTION_API_KEY>" \ "http://localhost:3001/decisions?project_id=<project_id>&history=true&limit=20" ```

Reference

How RoBrain compares

After you've seen the loop, you may want to know how RoBrain fits the broader landscape of AI memory tools. The short version:

  • Claude Code Auto-Memory captures per-user, per-machine. Bob's machine has no idea what Alice's machine learned.
  • Mem0 stores facts and resolves contradictions at the moment of insertion. It doesn't periodically scan the whole corpus for contradictions that emerge later.
  • Cloudflare Agent Memory offers shared team memory profiles but runs as a managed service on Cloudflare's infrastructure.
  • RoBrain captures decisions + rejected alternatives as structured data in your Postgres, runs a scheduled scan over the whole corpus to catch contradictions, and keeps both sides queryable when decisions change.

See RoBrain vs Claude Code Auto Memory and Comparisons for the detailed breakdown.

Free / self-hosted vs Rory Plans cloud

Comparisons

RoBrain vs Claude Code Auto Memory

Claude Code Auto memory is Anthropic’s native persistence: Claude writes notes as it works into machine-local markdown under ~/.claude/projects/…/memory/ (official docs). Roughly the first ~200 lines or 25 KB of MEMORY.md loads every session; deeper notes live in topic files Claude reads on demand with normal file tooling. It ships with Claude Code v2.1.59+ and needs no Docker or Postgres. That makes it the closest competitor to RoBrain’s “capture things without writing MEMORY.md yourself” story — but the shape of the data differs.

CapabilityClaude auto-memoryRoBrain
StorageLocal markdown files, per-user, per-machinePostgres, can be team-shared
Capture mechanismActive — Claude decides what to writeSystematic passive — every turn auto-classified, Claude doesn't decide
Cross-toolClaude Code onlyAny MCP-capable client (Claude Code, Cursor, etc.)
RecallLoads MEMORY.md index at session startAlways-on summary + semantic search via embeddings
Audit trailFiles onlyFull session turn history in DB
New developer joining the projectSees nothingInherits the team's accumulated memory immediately

When Auto memory is enough: solo dev, single editor (Claude Code), repo younger than ~6 months, and you’re fine curating markdown when notes drift.

When RoBrain is worth the overhead: you need vetoes and file-level provenance as data, semantic recall across months of history, invalidation when decisions reverse, multiple editors, or a shared / auditable store.

The two can coexist: Auto memory for lightweight scratch notes; RoBrain for canonical decisions you want to query, explain, and review.

RoBrain vs Zep

RoBrain and Zep answer different questions and work well together.

RoBrain captures architectural decisions — what was chosen, why, and what was explicitly ruled out as a structured queryable field. It answers: "what did we decide about this module, and what did we reject?"

Zep / Graphiti captures conversation history and entity relationships — it stores sessions, extracts facts, builds a temporal knowledge graph, and supports semantic retrieval across all of it. Zep can implicitly capture decisions too — the difference is that RoBrain surfaces rejected alternatives as a structured rejected[] field you can query directly, whereas in Zep they would live in conversation prose. For relationship queries — "how does the auth module connect to everything else?" — Zep's multi-strategy retrieval (semantic + graph traversal + BM25) is particularly strong.

A combined setup:

```bash

Troubleshooting

After setup, Sensing runs automatically whenever Claude Code is open. The MCP server is registered in ~/.claude/mcp.json, so Claude Code starts it automatically on launch. The CLAUDE.md instructions tell Claude to call sensing_start_session at the beginning of each session and sensing_record_turn after every exchange.

The one thing that can break it:

Claude Code doesn't always follow CLAUDE.md instructions reliably — this is the compliance problem from pre-launch testing. If Claude stops calling sensing_record_turn, Sensing goes silent. The way to check:

npx robrain status

That prints Perception connectivity and a Decisions: count for the current project (from GET /projects). If Decisions: 0 after a session where you expected captures, Claude may not have called the Sensing tools, or Perception rejected writes — run npx robrain review to confirm what is stored. The fix is often to make CLAUDE.md more explicit or remind Claude: "follow the RoBrain instructions in CLAUDE.md."

The practical reality:

The developer needs two habits: - npx robrain review after sessions where important decisions were made - npx robrain inject --copy before starting a new task that builds on prior work

Everything else — capture, extraction, storage, embedding — happens without you doing anything.

🎯 aiskill88 AI 点评 A 级 2026-05-27

高质量的开源AI工作流项目

📚 实用指南(长尾问题)
适合谁
  • 使用 Cursor 编辑器、希望提升 AI 编程效率的开发者
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
  • 构建多智能体协作系统的 Agent 开发者
  • 构建企业知识库 / RAG 检索应用的团队
  • 跨境业务、多语言内容运营团队
最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
  • 生产部署优先使用 Docker Compose 隔离依赖,并挂载 volume 持久化数据
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
  • Cursor rules 控制在 80 行内,否则模型上下文成本会显著上升
常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
  • 容器内无法访问宿主机 localhost — 使用 host.docker.internal
部署方案
  • Docker:robrain 提供官方镜像,docker compose up 一键启动
  • CLI:直接 npm install -g / pip install,命令行调用
  • 云端托管:可放在 Vercel / Railway / Fly.io 等 PaaS 平台
相关搜索
robrain 中文教程robrain 安装报错怎么办robrain MCP 配置robrain Docker 部署robrain Agent 工作流robrain 与同类工具对比robrain 最佳实践robrain 适合谁用

⚡ 核心功能

👥 适合谁
  • 使用 Cursor 编辑器、希望提升 AI 编程效率的开发者
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
  • 构建多智能体协作系统的 Agent 开发者
  • 构建企业知识库 / RAG 检索应用的团队
⭐ 最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
  • 生产部署优先使用 Docker Compose 隔离依赖,并挂载 volume 持久化数据
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
  • Cursor rules 控制在 80 行内,否则模型上下文成本会显著上升
⚠️ 常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
  • 容器内无法访问宿主机 localhost — 使用 host.docker.internal

👥 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
  • +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

该工具使用 NOASSERTION 协议,商用场景请仔细阅读协议条款,必要时咨询法律意见。

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

📄 NOASSERTION — 请查阅原始协议条款了解具体使用限制。

🔗 相关工具推荐

📰 相关 AI 新闻
🍿 AI 圈相关吃瓜
🗺️ 相关解决方案
🧩 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

robrain 是一款TypeScript开发的AI辅助工具。开源AI工作流:Open-source shared memory for teams using AI agents. Captures every decision and。⭐61 · TypeScript 主要应用场景包括:团队AI协作。
💡 AI Skill Hub 点评

经综合评估,智能工作流 在Agent工作流赛道中表现稳健,质量良好。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。

⬇️ 获取与下载
📚 深入学习 智能工作流
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 robrain
原始描述 开源AI工作流:Open-source shared memory for teams using AI agents. Captures every decision and。⭐61 · TypeScript
Topics ai-agentstypescriptcontext-engineering
GitHub https://github.com/adelinamart/robrain
License NOASSERTION
语言 TypeScript
🔗 原始来源
🐙 GitHub 仓库  https://github.com/adelinamart/robrain 🌐 官方网站  https://robrain.dev/

收录时间:2026-05-27 · 更新时间:2026-05-30 · License:NOASSERTION · AI Skill Hub 不对第三方内容的准确性作法律背书。