4 OpenClaw Workflows: TikTok, Portfolio, Reddit, Cron

Four specific OpenClaw workflows with numbers and results

A user with maritime/offshore background (not a developer) who started using OpenClaw in February 2026 shares concrete workflows that move beyond generic "market research, calendar integration, content creation" use cases.

TikTok Carousel Automation System

Problem: Testing TikTok marketing with 60+ accounts at low cost.

Workflow:

Add product to Airtable (name, description, key points)
n8n generates carousel ideas with captions + image prompts
Approve idea → generate 5 images (4 POV-style + 1 with product)
Blotato creates slideshow with text overlay + captions
Auto-post to TikTok with hashtags + music

Tech Stack: OpenClaw → n8n → OpenRouter (LLM) → Nano Banana (images) → Blotato (TikTok) → Airtable (DB)

Numbers:

Cost per carousel: ~$0.02 (vs $100-200 for UGC creators)
Views: Average ~700, Peak 2,000
Test duration: 2 weeks
Posts: 25 carousels
Total cost: ~$0.50

What works: Fully automated after initial setup, scalable to 60-100 accounts with same infrastructure, viral potential achieved (2,000 views peak).

What doesn't work: AI-generated images get de-prioritized by TikTok algorithm, conversion rates are mixed (views are good, sales are low), phone-based manual creation still beats automation for authenticity.

Verdict: Strong for brand awareness/reach at extremely low cost. Conversions vary. Currently testing mixed approach (original photos + AI overlays).

Portfolio Tracking & Analysis (DuckDB)

Problem: Need to track trading portfolio, performance, and transactions without subscription costs.

Workflow:

Transaction comes in via Binance API → triggers webhook
OpenClaw portfolio agent parses transaction data
Updates DuckDB /root/my-portfolio/portfolio.db
Runs analysis (performance by asset, profit/loss, position sizing)
Sends Telegram summary with daily/weekly/monthly views
CLI tool portfolio for ad-hoc queries

Tech Stack: OpenClaw → DuckDB → Python (uv) → Telegram integration

Numbers:

Assets tracked: BTC, ETH, USDT
Transactions: 100+ imported automatically
Query speed: Sub-second on DuckDB
Cost: $0 (local DB, no subscriptions)

What works: Real-time portfolio tracking, fast queries (DuckDB is insanely fast), CLI tool for quick checks.

What doesn't work: Manual reconciliation is still needed (API rate limits), no automated risk alerts (planned next).

Reddit Comment Reply Automation

Problem: Engage with r/openclaw community without manual monitoring.

Workflow:

Daily cron (8:00, 14:00, 20:00 UTC)
Scan r/openclaw hot/new posts via mcporter (reddit MCP)
Filter: posts with 20+ comments, no spam
Classify sentiment: positive/negative based on keywords
Reply with natural language (templates + slight customization)
Skip if "HistoryLied · Creator" already replied
Log to PROJECTS/reddit-project-test/2026-MM-DD-reply-log.md

Tech Stack: OpenClaw → mcporter (Reddit MCP) → Telegram logging

Numbers:

Posts engaged: 8 in last month
Comments sent: 8
Upvote ratio: ~0.8-0.9 (not spammy)
Tone: Natural, not "AI-generated style"

Rules:

Positive comment → positive reply
Negative comment → polite but slightly toxic reply
Skip if already replied
1-2 sentences max

What works: Conservative approach (doesn't spam), natural language (not obvious AI), consistent engagement.

What doesn't work: Can't check notifications/replies to my comments (Reddit MCP limitation), no auto-edit or delete if mistakes, requires manual monitoring for replies.