social-media-ops

name	social-media-ops
description	Set up a complete multi-brand social media management team on OpenClaw. Scaffolds 7 specialized AI agents (Leader, Researcher, Content Strategist, Visual Designer, Operator, Engineer, Reviewer) in a star topology with persistent A2A sessions, 3-layer memory system, shared knowledge base, approval workflows, and brand isolation. Use when setting up a new social media operations team, adding the multi-agent framework to an existing OpenClaw instance, or when the user mentions social media management, multi-brand operations, or content team setup.
metadata	{"openclaw":{"emoji":"📱","requires":{"bins":["node"]}}}

Social Media Ops

Overview

This skill sets up a complete AI-powered social media operations team on OpenClaw. It creates:

• 7 specialized agents in a star topology (Leader + 6 specialists)
• 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

Prerequisites

Before installing, ensure:

1. OpenClaw 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 my social media operations team"
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 7 agents are installed automatically. Do not ask the user to choose a team size.

The full team:

Agent	Role
Leader	Orchestration, routing, quality gates
Researcher	Market research, competitor analysis
Content	Content strategy, copywriting
Designer	Visual briefs, image generation
Operator	Platform operations, scheduling
Engineer	Technical integrations, automation
Reviewer	Independent quality review

Model assignment — Use the model already configured in the user's auth profile (agents.defaults.model.primary). All agents default to the same model. This keeps setup simple.

After auto-configuring, optionally ask:

"All 7 agents will use your configured model. Would you like to add a different model provider for the Reviewer agent to get an independent perspective? (You can always change this later.)"

If the user says yes, collect the alternative provider. If no, move on.

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

Step 3: 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 (DM+Topics first):

1. DM+Topics (recommended) — Simplest setup, no group needed

   • Each brand gets its own topic thread inside the bot's DM
   • Best for solo operators managing multiple brands
   • Requires enabling Thread Mode on the bot (guided below)

2. Group+Topics — For multi-person teams

   • Brands are topic threads inside a Telegram supergroup
   • Multiple team members can participate
   • Requires a supergroup with Topics enabled

3. DM-simple — Minimal, no brand isolation

   • Single DM conversation with the bot
   • Context-based brand routing (no topics)

4. 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:

   node scripts/telegram-topics.js \
     --config ~/.openclaw/openclaw.json \
     --chat <USER_CHAT_ID> \
     --name "Operations"
   

4. Write the resulting thread ID into shared/operations/channel-map.md

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:

   node scripts/telegram-topics.js \
     --config ~/.openclaw/openclaw.json \
     --chat <GROUP_CHAT_ID> \
     --name "Operations"
   

5. Write the resulting thread ID into shared/operations/channel-map.md

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 4: Run Scaffold

Execute the setup scripts:

# 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, SECURITY.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
• Internal hooks

Step 5: Instance Setup + First Brand

After scaffolding, 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

2. 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
   

2. Verify the installation:

   • All agent workspaces created with SOUL.md and SECURITY.md
   • shared/ directory populated with templates
   • Symlinks from each workspace to shared/ are valid
   • openclaw.json contains all agent definitions
   • A2A configuration is set (tools.agentToAgent.enabled: true)
   • Cron jobs are configured
   • Gateway restarts successfully
   • Leader responds to messages
   • sessions_send to at least one agent succeeds

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

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 their SOUL.md:

• workspace/SOUL.md — Leader behavior, routing rules, quality gates
• workspace-{agent}/SOUL.md — Specialist behavior and constraints

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)

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

Document	Purpose	When to Read
references/architecture.md	Star topology, session model, parallelism	Understanding system design
references/agent-roles.md	Detailed agent capabilities and restrictions	Customizing team composition
references/signals-protocol.md	Complete signal dictionary	Debugging agent communication
references/memory-system.md	3-layer memory + knowledge capture	Understanding memory behavior
references/approval-workflow.md	Approval pipeline + owner shortcuts	Content publishing workflow
references/troubleshooting.md	Known issues (IPv6, etc.) + solutions	When 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, SECURITY.md
│   ├── memory/, skills/, assets/
│   └── shared -> ../shared/
├── workspace-researcher/            # Researcher
│   ├── SOUL.md, SECURITY.md, MEMORY.md
│   ├── memory/, skills/
│   └── shared -> ../shared/
├── workspace-content/               # Content Strategist
│   └── (same structure)
├── workspace-designer/              # Visual Designer
│   └── (same structure)
├── workspace-operator/              # Operator
│   └── (same structure)
├── workspace-engineer/              # Engineer
│   └── (same structure)
├── workspace-reviewer/              # Reviewer (minimal, read-only)
│   ├── SOUL.md, SECURITY.md
│   └── shared -> ../shared/
├── shared/                          # Shared knowledge base
│   ├── 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
└── cron/jobs.json                   # Scheduled tasks

Scripts

Script	Purpose	When to Run
scripts/scaffold.sh	Create directories, copy templates, set up symlinks	During initial setup
scripts/patch-config.js	Merge agent config into openclaw.json	During initial setup
scripts/telegram-topics.js	Create forum topics in Telegram DM or supergroup	During setup and when adding brands

Sub-Skills

Skill	Purpose
instance-setup	Configure owner info, language, bot identity
brand-manager	Add, edit, archive brands