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Multi-Agent Brand Studio

Sets up a multi-agent AI-powered social media team with brand-isolated workspaces, approval workflows, shared knowledge base, and Telegram integration on Ope...
搭建多智能体AI社交媒体团队,支持品牌隔离工作区、审批工作流、共享知识库及Telegram集成。
kuan0808
内容创作 clawhub v1.0.3 1 版本 100000 Key: 无需
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概述

name: multi-agent-brand-studio

description: Use when setting up Multi-Agent Brand Studio on OpenClaw for multi-brand social media operations, approval-gated publishing, brand-isolated workspaces, or multi-agent content workflows.

metadata:

{

"openclaw": {

"emoji": "📱",

"requires": {

"bins": ["node"]

}

}

}


Multi-Agent Brand Studio

Overview

This skill sets up Multi-Agent Brand Studio, a complete AI-powered social media operations team on OpenClaw. It creates:

  • 5 specialized agents in a star topology (Leader + 4 specialists) + on-demand Reviewer
  • Persistent A2A sessions for context-preserving multi-agent workflows
  • 3-layer memory system (MEMORY.md + daily notes + shared knowledge base)
  • Shared knowledge base with brand profiles, operations guides, and domain knowledge
  • Approval workflow ensuring nothing publishes without owner approval
  • Brand isolation with per-brand channels, content guidelines, and asset directories
  • Cron automation for daily memory consolidation and weekly KB review

Optional Dependencies

  • Image generation tool for Creator agent: The Creator agent requires an image generation tool installed in its workspace-creator/skills/ directory to produce images. Recommended: nano-banana-pro (Gemini-based, free tier). Without it, Creator produces text visual briefs only and cannot generate images.

Prerequisites

Before installing, ensure:

  1. OpenClaw v2026.2.26+ is installed and openclaw onboard has been completed
  2. At least one auth profile exists (e.g., Anthropic API key)
  3. The ~/.openclaw/ directory exists

Quick Start

1. Install the skill (if not already in workspace/skills/)
2. Trigger setup: "Set up Multi-Agent Brand Studio"
3. Follow the interactive onboarding (6 steps, ~10 minutes)
4. Start creating content!

Onboarding Flow

When first triggered, this skill runs an interactive setup process.

Step 1: Prerequisites Check

Verify the environment is ready:

  • [ ] OpenClaw installed and openclaw onboard completed
  • [ ] ~/.openclaw/ directory exists
  • [ ] At least one auth profile configured

If any prerequisite is missing, guide the user to resolve it before continuing.

Step 2: Team Setup

All 5 agents are installed automatically. Do not ask the user to choose a team size.

The full team:

AgentRole
-------------
LeaderOrchestration, routing, quality gates
CreatorContent + visual (copywriting, image gen, platform formatting)
WorkerExecution for Leader (files, CLI, config, maintenance)
ResearcherMarket research, competitor analysis
EngineerTechnical integrations, automation

On-demand:

AgentRole
-------------
ReviewerIndependent quality review (spawned when needed)

Model — All agents inherit the model configured during openclaw onboard (at agents.defaults.model). No per-agent model setup is needed.

> Advanced note: If you later want to run a leaner team, re-run scaffold.sh --agents leader,creator,engineer to scaffold a subset.

Step 3: Run Scaffold

Execute the setup scripts to create all directories and files first:

# 1. Create directories, copy templates, set up symlinks
bash scripts/scaffold.sh \
  --skill-dir "$(pwd)"

# 2. Merge agent configuration into openclaw.json
node scripts/patch-config.js \
  --config ~/.openclaw/openclaw.json

The scaffold creates:

  • Agent workspace directories with SOUL.md, AGENTS.md, MEMORY.md
  • Shared knowledge base with all template files
  • Symlinks from each workspace to shared/
  • Sub-skills (instance-setup, brand-manager) in Leader's skills/
  • Cron job definitions

The config patcher merges into openclaw.json:

  • Agent definitions with model assignments and tool restrictions
  • A2A session configuration
  • QMD memory paths (only if QMD is installed — otherwise skipped with a suggestion)
  • Internal hooks

Step 4: Telegram Setup

This step uses a guided flow — do not ask the user for raw chat IDs or thread IDs.

Phase A: Confirm Bot Token

  1. Check openclaw.json for channels.telegram.botToken
  2. If present → skip to Phase B
  3. If missing → guide the user:
    • "Open Telegram, search for @BotFather"
    • "Send /newbot and follow the prompts to create a bot"
    • "Copy the bot token and paste it here"
    • Write the token into openclaw.json at channels.telegram.botToken

Phase B: Choose Channel Mode

Present the options in this order (Group+Topics first):

  1. Group+Topics (recommended) — Best for most setups
    • Brands are topic threads inside a Telegram supergroup
    • Works for both solo operators and multi-person teams
    • Requires a supergroup with Topics enabled
  1. DM+Topics — Private alternative, no group needed
    • Each brand gets its own topic thread inside the bot's DM
    • Requires enabling Thread Mode on the bot (guided below)
  1. DM-simple — Minimal, no brand isolation
    • Single DM conversation with the bot
    • Context-based brand routing (no topics)
  1. Group-simple — Group without brand isolation
    • Single group conversation
    • Context-based brand routing (no topics)

Phase C: Mode-Specific Setup

If DM+Topics:

  1. Guide the user to enable Thread Mode on their bot:
    • "Open Telegram, find @BotFather"
    • "Tap the Open button (bottom-left) to open the BotFather MiniApp"
    • "Select your bot in the MiniApp"
    • "Go to Bot Settings"
    • "Find Thread Mode and enable it"
    • "Come back and tell me when it's done"
  2. Once confirmed, use the bot token to get the user's chat ID:
    • "Send any message to your bot in Telegram"
    • Agent reads the incoming message context to extract the user's chat ID from {{From}}
    • Agent writes the chat ID into the channel config
  3. Create the Operations topic automatically:

```bash

node scripts/telegram-topics.js \

--config ~/.openclaw/openclaw.json \

--chat \

--name "Operations"

```

  1. Write the resulting thread ID into shared/operations/channel-map.md
  2. Update cron/jobs.json — replace {{OPERATIONS_CHANNEL}} with the actual Operations channel address (format: chatId:threadId, e.g., 123456789:7)

If Group+Topics:

  1. Check if the user already has a supergroup:
    • If not: guide them to create one (Create Group → toggle "Topics" on)
  2. Guide the user to add the bot to the group:
    • "Add your bot to the supergroup"
    • "Make the bot an admin with the Manage Topics permission"
    • "Send a message in the group"
  3. Agent reads the incoming message context to extract:
    • Group chat ID from {{To}}
    • Agent writes the chat ID into the channel config
  4. Create the Operations topic automatically:

```bash

node scripts/telegram-topics.js \

--config ~/.openclaw/openclaw.json \

--chat \

--name "Operations"

```

  1. Write the resulting thread ID into shared/operations/channel-map.md
  2. Update cron/jobs.json — replace {{OPERATIONS_CHANNEL}} with the actual Operations channel address (format: chatId:threadId, e.g., -100XXXXXXXXXX:7)

If DM-simple:

  1. "Send any message to your bot in Telegram"
  2. Agent reads the chat ID from the incoming message context
  3. Write chat ID into channel config — done

If Group-simple:

  1. Guide: "Add the bot to your group and send a message"
  2. Agent reads the group chat ID from the incoming message context
  3. Write chat ID into channel config — done

Step 5: Instance Setup + First Brand

After scaffolding and Telegram configuration, run the sub-skills:

  1. Instance Setup (instance-setup skill)
    • Owner name and timezone
    • Communication language (owner-facing)
    • Default content language
    • Bot identity (name, emoji, personality)
    • Updates: shared/INSTANCE.md, workspace/IDENTITY.md
  1. First Brand (brand-manager add)
    • Brand ID, display name, domain
    • Target market and content language
    • Topic creation (for Topics modes):
    • Agent calls scripts/telegram-topics.js to create a topic named after the brand
    • The script returns the thread ID
    • Agent writes the thread ID into shared/operations/channel-map.md and the brand config
    • For simple modes: no topic needed, skip thread ID
    • Creates: brand profile, content guidelines, domain knowledge file, asset directories

Step 6: Verification + Gateway Restart

  1. Restart gateway:

```

openclaw gateway restart

```

  1. Run diagnostics:

```

openclaw doctor

```

This validates: agent config, DM allowlist inheritance, session health, model availability, and workspace integrity.

  1. Additional checks:
    • [ ] Leader responds to messages
    • [ ] sessions_send to at least one agent succeeds

Optional: Enable QMD semantic memory

If patch-config.js reported "qmd binary not found" during Step 3, agents will use file-based memory (which works fine). To enable enhanced semantic search:

  • Say "Set up QMD" to run the qmd-setup sub-skill, which guides you through installation and configuration.

Suggested first tasks after setup:

  1. Fill in your brand profile: shared/brands/{brand_id}/profile.md
  2. Test content creation: "Write a Facebook post for {brand}"
  3. Add more brands: "Add a new brand"
  4. Set up posting schedule: fill in shared/operations/posting-schedule.md

Post-Installation

Async Dispatch Model (v2.0.0+)

Leader uses fully async dispatch (sessions_send with timeoutSeconds: 0) for all agent communication. This means:

  • Leader is never blocked waiting for an agent — always available to the owner.
  • Agents callback to Leader via sessions_send when done (event-driven, not polling). Leader processes callbacks per the "Agent Callback Protocol" flow in AGENTS.md.
  • Each task is tracked in a separate file: tasks/T-{YYYYMMDD}-{HHMM}.md. Completed tasks are archived to tasks/archive/.
  • Stale task detection is handled by a cron job (stale-task-check, every 10 minutes) that scans tasks/ for steps stuck in [⏳] state. Runs as Leader.
  • HEARTBEAT.md ships empty by default — periodic checks are handled by cron jobs instead of heartbeat polls.

Secrets Management (Optional)

For centralized API key management instead of scattered env vars:

openclaw secrets audit      # Check for plaintext secrets in config
openclaw secrets configure  # Set up secret entries
openclaw secrets apply      # Activate secrets
openclaw secrets reload     # Hot-reload without gateway restart

Adding More Brands

Use the brand-manager sub-skill:

  • "Add a new brand" — interactive brand creation (auto-creates topic for Topics modes)
  • "List brands" — show all active brands
  • "Archive {brand}" — deactivate a brand

Customizing Agents

Each agent's behavior is defined in two files:

  • SOUL.md — Persona, philosophy, boundaries, safety rules
  • AGENTS.md — Operating procedures, data handling, brand scope, tools

Modify these files to tune agent behavior for your specific needs.

Memory System

The 3-layer memory system works automatically:

  • MEMORY.md — Long-term curated memory (auto-updated by cron)
  • memory/YYYY-MM-DD.md — Daily activity logs
  • shared/ — Permanent knowledge base (grows over time)

Optional enhancement: Install QMD for semantic search across the knowledge base. Use the qmd-setup sub-skill or install manually (bun install -g @tobilu/qmd).

See references/memory-system.md for detailed documentation.

Communication Signals

Agents use standardized signals to communicate status. See references/signals-protocol.md for the complete signal dictionary.

Reference Documentation

DocumentPurposeWhen to Read
--------------------------------
references/architecture.mdStar topology, session model, parallelismUnderstanding system design
references/agent-roles.mdDetailed agent capabilities and restrictionsCustomizing team composition
references/signals-protocol.mdComplete signal dictionaryDebugging agent communication
references/memory-system.md3-layer memory + knowledge captureUnderstanding memory behavior
references/approval-workflow.mdApproval pipeline + owner shortcutsContent publishing workflow
references/troubleshooting.mdKnown issues (IPv6, etc.) + solutionsWhen something breaks

Directory Structure

After installation, the following structure is created:

~/.openclaw/
├── openclaw.json                    # Updated with agent configs
├── workspace/                       # Leader
│   ├── SOUL.md, AGENTS.md, HEARTBEAT.md, IDENTITY.md
│   ├── memory/, skills/, assets/
│   └── shared/                      # Real directory (shared KB lives here)
│       ├── INSTANCE.md              # Instance configuration
│       ├── brand-registry.md        # Brand registry
│       ├── system-guide.md, brand-guide.md, compliance-guide.md
│       ├── team-roster.md
│       ├── brands/{id}/profile.md   # Per-brand profiles
│       ├── domain/{id}-industry.md  # Industry knowledge
│       ├── operations/              # Ops guides
│       └── errors/solutions.md      # Error KB
├── workspace-creator/               # Creator
│   ├── SOUL.md, AGENTS.md, MEMORY.md
│   ├── memory/, skills/
│   └── shared -> ../workspace/shared/
├── workspace-worker/                # Worker
│   └── (same structure)
├── workspace-researcher/            # Researcher
│   └── (same structure)
├── workspace-engineer/              # Engineer
│   └── (same structure)
├── workspace-reviewer/              # Reviewer (minimal, read-only)
│   ├── SOUL.md, AGENTS.md
│   └── shared -> ../workspace/shared/
└── cron/jobs.json                   # Scheduled tasks

Scripts

ScriptPurposeWhen to Run
------------------------------
scripts/scaffold.shCreate directories, copy templates, set up symlinksDuring initial setup
scripts/patch-config.jsMerge agent config into openclaw.jsonDuring initial setup
scripts/telegram-topics.jsCreate forum topics in Telegram DM or supergroupDuring setup and when adding brands

Sub-Skills

SkillPurpose
----------------
instance-setupConfigure owner info, language, bot identity
brand-managerAdd, edit, archive brands
qmd-setupInstall and configure QMD semantic search memory (optional)

版本历史

共 1 个版本

  • v1.0.3 当前
    2026-03-19 14:40 安全 安全

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