Social Media Ops

Overview

This skill sets up 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:

OpenClaw v2026.2.26+ is installed and openclaw onboard has been completed
At least one auth profile exists (e.g., Anthropic API key)
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 5 agents are installed automatically. Do not ask the user to choose a team size.

The full team:

| Agent | Role | |-------|------| | Leader | Orchestration, routing, quality gates | | Creator | Content + visual (copywriting, image gen, platform formatting) | | Worker | Execution for Leader (files, CLI, config, maintenance) | | Researcher | Market research, competitor analysis | | Engineer | Technical integrations, automation |

On-demand:

| Agent | Role | |-------|------| | Reviewer | Independent 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

Check openclaw.json for channels.telegram.botToken
If present → skip to Phase B
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):

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
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)
DM-simple — Minimal, no brand isolation
- Single DM conversation with the bot
- Context-based brand routing (no topics)
Group-simple — Group without brand isolation
- Single group conversation
- Context-based brand routing (no topics)

Phase C: Mode-Specific Setup

If DM+Topics:

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"
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

Create the Operations topic automatically:

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

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

If Group+Topics:

Check if the user already has a supergroup:
- If not: guide them to create one (Create Group → toggle "Topics" on)
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"
Agent reads the incoming message context to extract:
- Group chat ID from {{To}}
- Agent writes the chat ID into the channel config

Create the Operations topic automatically:

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

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

If DM-simple:

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

If Group-simple:

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

Step 5: Instance Setup + First Brand

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

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
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

Restart gateway:
```
openclaw gateway restart
```
Run diagnostics:
```
openclaw doctor
```
This validates: agent config, DM allowlist inheritance, session health, model availability, and workspace integrity.
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:

Fill in your brand profile: shared/brands/{brand_id}/profile.md
Test content creation: "Write a Facebook post for {brand}"
Add more brands: "Add a new brand"
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

| 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
│   ├── 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

| 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 | | qmd-setup | Install and configure QMD semantic search memory (optional) |