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🦀 ClawHub

Team Builder

by @beyound87

在 OpenClaw 上一键部署多 Agent SaaS 团队工作区。内置双开发轨(devops 交付 + fullstack-dev 实现)、实时 spawn 调度、cron 巡检、Deep Dive 产品知识目录、onboarding 引导。支持自定义角色、模型、时区,可选 Telegram 接入。

Versionv3.0.0
Downloads1,329
Installs8
TERMINAL
clawhub install team-builder

📖 About This Skill


name: team-builder description: 在 OpenClaw 上一键部署多 Agent SaaS 团队工作区。内置双开发轨(devops 交付 + fullstack-dev 实现)、实时 spawn 调度、cron 巡检、Deep Dive 产品知识目录、onboarding 引导。支持自定义角色、模型、时区,可选 Telegram 接入。

Team Builder

一条命令部署完整多 Agent 团队骨架,包含角色、信箱、看板、产品知识目录、cron 巡检、双开发轨模板。

> 详细安装步骤和首次配置引导见 README.md(中文完整版)。

前置条件

  • OpenClaw 已安装并运行
  • Node.js 16+
  • 已配置至少一个模型 provider
  • > 此技能会修改系统配置apply-config.js 会写入 openclaw.jsoncreate-crons.* 会创建 cron 任务。均需手动执行,不自动运行。

    Internal Dispatch Protocol (MANDATORY)

  • Standard agents (product-lead, growth-lead, intel-analyst, devops, etc.): sessions_spawn(runtime="subagent", mode="run")禁止带 streamTo
  • ACP agents (fullstack-dev): sessions_spawn(runtime="acp") — 可带 streamTo="parent"
  • 结果通过 auto-announce 推送;不要轮询 sessions_listsubagents list
  • chief-of-staff 是群内唯一入口;其他 agent 内部 spawn,不直接监听群聊
  • 详见 shared/knowledge/team-workflow.md 零章
  • 参谋长执行边界(MANDATORY)

  • 参谋长不下地干活:任何多步骤任务(编码、调研、分析、内容、部署)→ 全部派给对应 agent
  • 参谋长不亲自开子代理干活:spawn 子代理执行具体业务 = 等价于自己干活
  • 参谋长做且只做:任务拆解(L1-L4 复杂度判断)、编排、派活、监控、结果汇总
  • 先执行后汇报;默认输出只保留:已做什么 / 拿到什么结果 / 卡在哪里
  • 子代理使用规则(MANDATORY,全团队适用)

  • 优先主 agent 自己干:干得过来时不开子代理
  • 分析透再派:开子代理前必须先分析清楚边界/依赖/输入输出
  • 子代理只做原子任务:一句话说清、执行完就结束,不做判断或策略决策
  • 主 agent 全权负责:判断、策略、经验积累——子代理不做这三件
  • 子代理结果由主 agent 汇总后再上报参谋长
  • Credentials involved

  • Telegram bot tokens (optional) -- stored in openclaw.json, used for agent-to-Telegram binding
  • Model API keys -- must already be configured in your OpenClaw model providers (not handled by this skill)
  • Recommended

  • Review generated apply-config.js before running
  • Check the backup of openclaw.json after running
  • Test with 2-3 agents before enabling all cron jobs
  • Team Architecture

    Default reference architecture for a SaaS/growth multi-agent team (customizable to 2-10 agents):

    CEO
     |-- Chief of Staff (dispatch + strategy + efficiency)
     |-- Data Analyst (data + user research)
     |-- Growth Lead (GEO + SEO + community + social media)
     |-- Content Chief (strategy + writing + copywriting + i18n)
     |-- Intel Analyst (competitor monitoring + market trends)
     |-- Product Lead (product management + tech architecture)
     |-- DevOps (delivery / deploy / environment / acceptance)
     |-- Fullstack Dev (implementation / module deep dive / ACP coding session)
    

    Multi-Team Support

    One OpenClaw instance can run multiple teams:

    node /scripts/deploy.js                  # default team
    node /scripts/deploy.js --team alpha      # named team "alpha"
    node /scripts/deploy.js --team beta       # named team "beta"
    

    Named teams use prefixed agent IDs (alpha-chief-of-staff, beta-growth-lead) to avoid conflicts. Each team gets its own workspace subdirectory.

    Flexible Team Size

    The wizard lets you select 2-10 agents from the available roles. Skip roles you don't need. The 8-agent default covers most SaaS scenarios with dual-dev routing, but you can run leaner (3-4 agents) or expand with custom roles.

    Model Auto-Detection

    The wizard scans your openclaw.json for registered model providers and auto-suggests models by role type:

    | Role Type | Best For | Auto-detect Pattern | |-----------|----------|-------------------| | Thinking | Strategic roles (chief, growth, content, product) | /glm-5\|opus\|o1\|deepthink/i | | Execution | Operational roles (data, intel, fullstack) | /glm-4\|sonnet\|gpt-4/i | | Fast | Lightweight tasks | /flash\|haiku\|mini/i |

    You can always override with manual model IDs.

    Setup / Config / Scripts

    Required Inputs

  • Team name
  • Workspace dir
  • Timezone
  • Morning brief hour
  • Evening brief hour
  • Thinking model
  • Execution model
  • CEO title
  • Optional Inputs

  • Telegram user ID
  • Telegram bot tokens
  • Proxy
  • ACP coding agent(给 fullstack-dev 使用)
  • Core Scripts

    node /scripts/deploy.js
    node /apply-config.js
    powershell /create-crons.ps1
    bash /create-crons.sh
    openclaw gateway restart
    

    Execution Priority

  • First: matched execution skill (for coding work, coding-lead if loaded)
  • Second: agent-role fallback when no matching skill is loaded
  • Third: templates/README explain boundaries and ownership only; they should not override matched skills
  • Context File Hygiene

  • Active context files live under /.openclaw/
  • Reuse one context file per active code chain when possible
  • Naming pattern: context-.md
  • Active context file cap per project: 60
  • Context-file lifecycle window per project: 100 total files across active + archive
  • Completed or stale files should be deleted or moved to .openclaw/archive/
  • Current Dual-Dev Standard

  • fullstack-dev:实现、模块深挖、开发文档、接口文档、Claude coding 执行;默认 coding skill 可采用 coding-lead,其中 simple 任务直做,medium 倾向 Claude ACP run 或 direct acpx,complex 通过现有会话连续协作 + 上下文文件推进,不把 ACP session 持久线程作为正式主路径;context 活跃上限 60、生命周期总窗口 100;并行允许但必须先定义边界,总上限 5 个工作单元
  • devops:交付、部署、环境、回归、冒烟、自动QA、发布门禁
  • product-lead:澄清、PRD、验收标准,不完整不得派工
  • chief-of-staff:路由、裁决、控制 token 浪费
  • 部署流程

    > 完整步骤见 README.md。以下是关键参数选取对照表。

    必填参数

    | 参数 | 默认值 | 说明 | |--------|--------|------| | teamName | Alpha Team | 团队名 | | workspaceDir | ~/.openclaw/workspace-team | 工作区路径 | | timezone | Asia/Shanghai | cron 时区 | | morningHour | 8 | 晨报时间 | | eveningHour | 18 | 晚报时间 | | thinkingModel | 自动检测 | 策略型角色(chief/product/growth/content)| | executionModel | 自动检测 | 执行型角色(devops/fullstack/intel/data)| | ceoTitle | Boss | CEO 称呼 |

    可选参数

  • roles:自定义角色列表(默认全郥 8 个)
  • roleNames:自定义角色名称(如中文起名)
  • --team :多团队并存时用于隔离角色 ID
  • Telegram bot tokens(可选,配置后自动写入 openclaw.json)
  • 核心命令

    # 交互式生成
    node /scripts/deploy.js

    非交互生成

    node /scripts/deploy.js --config team-builder.json

    验证生成结果

    node /scripts/deploy.js --verify --config team-builder.json

    应用配置(写入 openclaw.json)

    node /apply-config.js

    创建 cron

    powershell /create-crons.ps1 # Windows bash /create-crons.sh # macOS/Linux

    重启

    openclaw gateway restart

    --verify 检查生成物是否包含双开发模型、角色归属、cron 条目。

    完整安装步骤见 README.md

    Cron Schedule

    | Offset | Agent | Task | Frequency | |--------|-------|------|-----------| | H-1 | Data Analyst | Data + user feedback | Daily | | H-1 | Intel Analyst | Competitor scan | Mon/Wed/Fri | | H | Chief of Staff | Morning brief (announced) | Daily | | H+1 | Growth Lead | GEO + SEO + community | Daily | | H+1 | Content Chief | Weekly content plan | Monday | | H+2 | DevOps | Delivery / environment / Deep Dive / acceptance | Daily | | H+10 | Chief of Staff | Evening brief (announced) | Daily |

    (H = morning brief hour)

    Generated File Structure

    /
    ├── AGENTS.md, SOUL.md, USER.md  (auto-injected)
    ├── apply-config.js, create-crons.ps1/.sh, README.md
    ├── agents/<8 agent dirs>/       (SOUL.md + MEMORY.md + memory/)
    └── shared/
        ├── briefings/, decisions/, inbox/ (v2: with status tracking)
        ├── status/team-dashboard.md     (chief-of-staff maintains, all agents read first)
        ├── data/                        (public data pool, data-analyst writes, all read)
        ├── kanban/, knowledge/
        └── products/
            ├── _index.md                (product matrix overview)
            ├── _template/               (knowledge directory template)
            └── {product}/               (per-product knowledge, up to 20 files)
                ├── overview.md, architecture.md, database.md, api.md, routes.md
                ├── models.md, services.md, frontend.md, auth.md, integrations.md
                ├── jobs-events.md, config-env.md, dependencies.md, devops.md
                ├── test-coverage.md, tech-debt.md, domain-flows.md, data-flow.md
                ├── i18n.md, changelog.md, notes.md
    

    Knowledge Governance

    Each shared knowledge file has a designated owner. Only the owner agent updates it; others read only.

    | File | Owner | Update Trigger | |------|-------|---------------| | geo-playbook.md | growth-lead | After GEO experiments/discoveries | | seo-playbook.md | growth-lead | After SEO experiments | | competitor-map.md | intel-analyst | After each competitor scan | | content-guidelines.md | content-chief | After proven writing patterns | | user-personas.md | data-analyst | After new user insights | | tech-standards.md | product-lead | After architecture decisions |

    Update Protocol

    When updating a knowledge file, the owner must: 1. Add a dated entry at the top: ## [YYYY-MM-DD] 2. Include the reason and data evidence 3. Never delete existing entries without CEO approval (append, don't replace)

    Chief of Staff Governance

    The chief-of-staff monitors knowledge file health during weekly reviews:
  • Are files being updated regularly?
  • Any conflicting information between files?
  • Any stale entries that should be archived?
  • Self-Evolution Pattern

    Agents improve their own strategies over time through a feedback loop:

    1. Execute task (cron or inbox triggered)
    2. Collect results (data, metrics, outcomes)
    3. Analyze: what worked vs what didn't
    4. Update knowledge files with proven strategies (with evidence)
    5. Next execution reads updated knowledge → better performance
    

    This is NOT the agent randomly changing rules. Updates must be:

  • Data-driven: backed by metrics or concrete outcomes
  • Incremental: append new findings, don't rewrite everything
  • Traceable: dated with evidence so others can verify
  • What Agents Can Self-Update

  • Their own knowledge files (per ownership table above)
  • Their own MEMORY.md (lessons learned, decisions)
  • shared/data/ outputs (data-analyst only)
  • What Requires CEO Approval

  • shared/decisions/active.md (strategy changes)
  • Adding/removing agents or changing team architecture
  • External publishing or spending decisions
  • Public Data Layer

    The shared/data/ directory serves as a read-only data pool for all agents:

  • data-analyst writes: daily metrics, user feedback summaries, anomaly alerts
  • All agents read: to inform their own decisions
  • Format: structured markdown or JSON, dated filenames (e.g., metrics-2026-03-01.md)
  • Retention: keep 30 days, archive older files
  • Project Deep Dive - Code Scanning

    Agents can deeply understand each SaaS product through automated code scanning. This is critical - without deep project knowledge, all team decisions are surface-level.

    How It Works

    1. CEO adds a product to shared/products/_index.md (name, URL, code directory, tech stack) 2. Product Lead triggers a delivery-oriented Deep Dive scan by dispatching to DevOps (via sessions_spawn if online, inbox as fallback) 3. DevOps enters the project directory (read-only) and generates shared knowledge / delivery-oriented scan outputs 4. Fullstack Dev picks up module-level deep dive or implementation follow-up when needed 5. Knowledge files are generated in shared/products/{product}/ 6. All agents consume these files via manifest-based lazy loading (never read all at once)

    Manifest-Based Lazy Loading (MANDATORY)

    Each product directory includes a manifest.json (~200 tokens) that lists all files with one-line summaries and a taskFileMap mapping task types to relevant files.

    Agent workflow: 1. Read _index.md → identify which product 2. Read {product}/manifest.json → see all files + summaries (~200 tokens) 3. Based on taskFileMap or summaries, read only 1-3 relevant files 4. Never read more than 5 product files per session

    Why: With 15+ products × 20 files each, full loading = 40K+ tokens per product. Manifest loading = 200 tokens + only what's needed.

    DevOps MUST regenerate manifest.json after every delivery-oriented scan (L0-L4). Fullstack Dev updates it when doing module-level follow-up that changes knowledge scope. Template in _template/manifest.json.

    Manifest Quality Standards

    摘要不能为了省 token 丢掉关键信息。每条摘要须满足:

  • 核心文件(database/models/services/routes/integrations):50-130字,列出关键实体名/数量/域名
  • 中等文件(auth/frontend/commands/config):30-80字,点明方案和范围
  • 轻量文件(changelog/notes/metrics):可以短(<20字)
  • taskFileMap:必须覆盖该产品的所有核心业务场景(不少于8个映射)
  • codeStats:必须包含文件数、行数、模型数、表数等量化指标
  • Product Knowledge Directory

    Each product gets a knowledge directory with up to 20 files + manifest:

    shared/products/{product}/
    ├── manifest.json        ← INDEX (~200 tokens): file list, summaries, taskFileMap
    ├── overview.md          ← Product positioning (from _index.md)
    ├── architecture.md      ← System architecture, tech stack, design patterns, layering
    ├── database.md          ← Full table schema, relationships, indexes, migrations
    ├── api.md               ← API endpoints, params, auth, versioning
    ├── routes.md            ← Complete route table (Web + API + Console)
    ├── models.md            ← ORM relationships, scopes, accessors, observers
    ├── services.md          ← Business logic, state machines, workflows, validation
    ├── frontend.md          ← Component tree, page routing, state management
    ├── auth.md              ← Auth scheme, roles/permissions matrix, OAuth
    ├── integrations.md      ← Third-party: payment/email/SMS/storage/CDN/analytics
    ├── jobs-events.md       ← Queue jobs, event listeners, scheduled tasks, notifications
    ├── config-env.md        ← Environment variables, feature flags, cache strategy
    ├── dependencies.md      ← Key dependencies, custom packages, vulnerabilities
    ├── devops.md            ← Deployment, CI/CD, Docker, monitoring, logging
    ├── test-coverage.md     ← Test strategy, coverage, weak spots
    ├── tech-debt.md         ← TODO/FIXME/HACK inventory, dead code, complexity hotspots
    ├── domain-flows.md      ← Core user journeys, domain boundaries, module coupling
    ├── data-flow.md         ← Data lifecycle: external → import → process → store → output
    ├── i18n.md              ← Internationalization, language coverage
    ├── changelog.md         ← Scan diff log (what changed between scans)
    └── notes.md             ← Agent discoveries, gotchas, implicit rules
    

    Scan Levels

    | Level | Scope | When | Output | |-------|-------|------|--------| | L0 Snapshot | Surface: directory tree, packages, env | First onboard | architecture, dependencies, config-env | | L1 Skeleton | Structure: DB, routes, models, components | First onboard | database, routes, api, models, frontend | | L2 Deep Dive | Logic: services, auth, jobs, integrations | On-demand per module | services, auth, jobs-events, integrations, domain-flows, data-flow | | L3 Health Check | Quality: tech debt, tests, security | Periodic / pre-release | tech-debt, test-coverage, devops | | L4 Incremental | Delta: git diff → update affected files | After code changes | changelog + targeted updates |

    Content Standards

    Knowledge files capture not just WHAT exists but WHY:

  • Design decisions: Why this approach was chosen
  • Implicit business rules: Logic buried in code (e.g., "orders auto-cancel after 72h")
  • Gotchas: What breaks if you touch this module carelessly
  • Cross-module coupling: Where changing A silently breaks B
  • Performance hotspots: N+1 queries, missing indexes, bottleneck endpoints
  • Role Responsibilities

    | Role | Responsibility | |------|---------------| | Product Lead | Clarification / PRD / acceptance: complete clarification, PRD, user stories, acceptance criteria, and review knowledge freshness before delegating | | DevOps | Delivery / QA gate / Deep Dive: enter code directory for deployment-oriented scans, maintain release checklist, smoke/regression testing, auto-QA access, and generate/update shared product knowledge files | | Fullstack Dev | Implementation / docs / Deep Dive follow-up: continue module-level deep dive, code analysis, implementation, dev docs, interface docs, and ACP session work | | Chief of Staff | Routing / escalation: split implementation vs delivery tasks, prevent duplicate labor, escalate blockers | | All Agents | Consumption: read product knowledge before any product-related decision |

    Per-Stack Auto-Detection

    Fullstack Dev auto-detects tech stack and applies stack-specific scan strategies:

  • Laravel/PHP: migrations, route:list, Models, Services, Middleware, Policies, Jobs, Console/Kernel
  • React/Vue: components, router, stores, API client, i18n
  • Python/Django/FastAPI: models.py, urls.py, views.py, middleware, celery
  • General: tree, git log, grep TODO/FIXME, .env.example, Docker, CI, tests
  • Team Coordination v2

    Inbox Protocol v2 (backup channel, status tracking)

    > Primary dispatch: sessions_spawn (real-time). Inbox is for archival, cross-session handoff, and fallback when spawn is unavailable.

    Every inbox message now has a status field:

  • pendingreceivedin-progressdone (or blocked)
  • Chief-of-staff monitors timeouts: high>4h, normal>24h pending = intervention
  • Blocked >8h = escalation to CEO
  • Recipients MUST update status immediately upon reading
  • Team Dashboard (shared/status/team-dashboard.md)

    Chief-of-staff maintains a "live scoreboard" updated every session:

  • 🔴 Urgent/Blocked items
  • 📊 Per-agent status table (last active, current task, status icon)
  • 📬 Unprocessed inbox summary (pending/blocked messages across all inboxes)
  • 🔗 Cross-agent task chain tracking (A→B→C with per-step status)
  • 📅 Today/Tomorrow focus
  • Agent 启动顺序(内置于 AGENTS.md): 1. 确认角色 2. 读 agents/[role]/SOUL.md 3. 读 shared/onboarding.md(项目背景,CEO 填写) 4. 读 shared/status/team-dashboard.md(当前状态) 5. 读 shared/decisions/active.md(仅涉及策略时) 6. 读 shared/inbox/to-[role].md 7. 读 agents/[role]/MEMORY.md(仅需历史上下文时)

    Chief-of-Staff as Router

    The chief is upgraded from "briefing writer" to "active team router":

  • Real-time dispatch: uses sessions_spawn(runtime="subagent") to directly wake agents and assign tasks - this is the primary dispatch method
  • Blocker detection: scans all inboxes for overdue messages
  • Inbox as backup: writes to inbox only for archival, cross-session handoff, or when agent is unreachable
  • Task chain tracking: identifies multi-agent workflows and tracks each step
  • Escalation: persistent blockers get flagged to CEO
  • Runs 4x/day (morning brief, midday patrol, afternoon patrol, evening brief)
  • Cron Schedule (10 jobs, up from 7)

    | Time | Agent | Type | Purpose | |------|-------|------|---------| | 07:00 | data-analyst | daily | Data pull + feedback scan | | 08:00 | chief-of-staff | announce | Morning: router scan + brief + quality | | 09:00 | growth-lead | daily | GEO/SEO/community | | 09:00 | product-lead | daily (NEW) | Inbox + clarification/PRD + task delegation | | 10:00 | content-chief | daily M-F (was weekly) | Content creation + collaboration | | 10:00 | devops | daily (delivery track) | Inbox + Deep Dive + delivery + QA gate | | 12:00 | chief-of-staff | patrol (NEW) | Router scan only, no brief | | 15:00 | chief-of-staff | patrol (NEW) | Router scan only, no brief | | 18:00 | chief-of-staff | announce | Evening: router scan + summary + next day plan | | 07:00 M/W/F | intel-analyst | 3x/week | Competitor scan |

    Why These Changes Matter

    | Before | After | Impact | |--------|-------|--------| | Inbox = primary dispatch | Inbox = backup + spawn = primary | Real-time dispatch via spawn; inbox for archival only | | Chief 2x/day | Chief 4x/day with router role | Blockers caught within hours, not days | | Content-chief 1x/week | Daily M-F | Actually produces content | | Product-lead no cron | Daily | Knowledge governance happens | | No team dashboard | Dashboard every session | All agents know the full picture | | No timeout detection | Automatic timeout rules | Nothing falls through cracks |

    Key Design Decisions

  • Shared workspace so qmd indexes everything for all agents
  • Real-time spawn dispatch as primary inter-agent communication; inbox as backup for archival and cross-session handoff
  • Chief as Router - active coordinator who dispatches via sessions_spawn, detects blockers, and resolves them
  • Team Dashboard - single source of truth for team-wide status, maintained by chief every session
  • GEO as #1 priority (AI search = blue ocean)
  • Fullstack Dev spawns Claude Code via ACP for complex implementation tasks
  • DevOps owns delivery and QA gate so implementation and release responsibilities stay separated
  • Project Deep Dive gives all agents deep codebase understanding, not just surface-level product overviews
  • Customization

    Edit ROLES array in scripts/deploy.js to add/remove agents. Edit references/soul-templates.md for SOUL.md templates. Edit references/shared-templates.md for shared file templates.