Add 3 new use cases: Polymarket Autopilot, Project State Management, Dynamic Dashboard

usecases/dynamic-dashboard.md

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+# Dynamic Dashboard with Sub-agent Spawning
+
+Static dashboards show stale data and require constant manual updates. You want real-time visibility across multiple data sources without building a custom frontend or hitting API rate limits.
+
+This workflow creates a live dashboard that spawns sub-agents to fetch and process data in parallel:
+
+• Monitors multiple data sources simultaneously (APIs, databases, GitHub, social media)
+• Spawns sub-agents for each data source to avoid blocking and distribute API load
+• Aggregates results into a unified dashboard (text, HTML, or Canvas)
+• Updates every N minutes with fresh data
+• Sends alerts when metrics cross thresholds
+• Maintains historical trends in a database for visualization
+
+## Pain Point
+
+Building a custom dashboard takes weeks. By the time it's done, requirements have changed. Polling multiple APIs sequentially is slow and hits rate limits. You need insight now, not after a weekend of coding.
+
+## What It Does
+
+You define what you want to monitor conversationally: "Track GitHub stars, Twitter mentions, Polymarket volume, and system health." OpenClaw spawns sub-agents to fetch each data source in parallel, aggregates the results, and delivers a formatted dashboard to Discord or as an HTML file. Updates run automatically on a cron schedule.
+
+Example dashboard sections:
+- **GitHub**: stars, forks, open issues, recent commits
+- **Social Media**: Twitter mentions, Reddit discussions, Discord activity
+- **Markets**: Polymarket volume, prediction trends
+- **System Health**: CPU, memory, disk usage, service status
+
+## Skills Needed
+
+- Sub-agent spawning for parallel execution
+- `github` (gh CLI) for GitHub metrics
+- `bird` (Twitter) for social data
+- `web_search` or `web_fetch` for external APIs
+- `postgres` for storing historical metrics
+- Discord or Canvas for rendering the dashboard
+- Cron jobs for scheduled updates
+
+## How to Set it Up
+
+1. Set up a metrics database:
+```sql
+CREATE TABLE metrics (
+  id SERIAL PRIMARY KEY,
+  source TEXT, -- e.g., "github", "twitter", "polymarket"
+  metric_name TEXT,
+  metric_value NUMERIC,
+  timestamp TIMESTAMPTZ DEFAULT NOW()
+);
+
+CREATE TABLE alerts (
+  id SERIAL PRIMARY KEY,
+  source TEXT,
+  condition TEXT,
+  threshold NUMERIC,
+  last_triggered TIMESTAMPTZ
+);
+```
+
+2. Create a Discord channel for dashboard updates (e.g., #dashboard).
+
+3. Prompt OpenClaw:
+```text
+You are my dynamic dashboard manager. Every 15 minutes, run a cron job to:
+
+1. Spawn sub-agents in parallel to fetch data from:
+   - GitHub: stars, forks, open issues, commits (past 24h)
+   - Twitter: mentions of "@username", sentiment analysis
+   - Polymarket: volume for tracked markets
+   - System: CPU, memory, disk usage via shell commands
+
+2. Each sub-agent writes results to the metrics database.
+
+3. Aggregate all results and format a dashboard:
+
+📊 **Dashboard Update** — [timestamp]
+
+**GitHub**
+- ⭐ Stars: [count] (+[change])
+- 🍴 Forks: [count]
+- 🐛 Open Issues: [count]
+- 💻 Commits (24h): [count]
+
+**Social Media**
+- 🐦 Twitter Mentions: [count]
+- 📈 Sentiment: [positive/negative/neutral]
+
+**Markets**
+- 📊 Polymarket Volume: $[amount]
+- 🔥 Trending: [market names]
+
+**System Health**
+- 💻 CPU: [usage]%
+- 🧠 Memory: [usage]%
+- 💾 Disk: [usage]%
+
+4. Post to Discord #dashboard.
+
+5. Check alert conditions:
+   - If GitHub stars change > 50 in 1 hour → ping me
+   - If system CPU > 90% → alert
+   - If negative sentiment spike on Twitter → notify
+
+Store all metrics in the database for historical analysis.
+```
+
+4. Optional: Use Canvas to render an HTML dashboard with charts and graphs.
+
+5. Query historical data: "Show me GitHub star growth over the past 30 days."
+
+## Related Links
+
+- [Parallel Processing with Sub-agents](https://docs.openclaw.ai/subagents)
+- [Dashboard Design Principles](https://www.nngroup.com/articles/dashboard-design/)