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114 lines
3.8 KiB
Markdown
114 lines
3.8 KiB
Markdown
# Dynamic Dashboard with Sub-agent Spawning
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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.
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This workflow creates a live dashboard that spawns sub-agents to fetch and process data in parallel:
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• Monitors multiple data sources simultaneously (APIs, databases, GitHub, social media)
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• Spawns sub-agents for each data source to avoid blocking and distribute API load
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• Aggregates results into a unified dashboard (text, HTML, or Canvas)
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• Updates every N minutes with fresh data
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• Sends alerts when metrics cross thresholds
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• Maintains historical trends in a database for visualization
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## Pain Point
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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.
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## What It Does
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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.
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Example dashboard sections:
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- **GitHub**: stars, forks, open issues, recent commits
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- **Social Media**: Twitter mentions, Reddit discussions, Discord activity
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- **Markets**: Polymarket volume, prediction trends
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- **System Health**: CPU, memory, disk usage, service status
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## Skills Needed
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- Sub-agent spawning for parallel execution
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- `github` (gh CLI) for GitHub metrics
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- `bird` (Twitter) for social data
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- `web_search` or `web_fetch` for external APIs
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- `postgres` for storing historical metrics
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- Discord or Canvas for rendering the dashboard
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- Cron jobs for scheduled updates
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## How to Set it Up
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1. Set up a metrics database:
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```sql
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CREATE TABLE metrics (
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id SERIAL PRIMARY KEY,
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source TEXT, -- e.g., "github", "twitter", "polymarket"
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metric_name TEXT,
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metric_value NUMERIC,
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timestamp TIMESTAMPTZ DEFAULT NOW()
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);
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CREATE TABLE alerts (
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id SERIAL PRIMARY KEY,
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source TEXT,
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condition TEXT,
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threshold NUMERIC,
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last_triggered TIMESTAMPTZ
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);
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```
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2. Create a Discord channel for dashboard updates (e.g., #dashboard).
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3. Prompt OpenClaw:
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```text
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You are my dynamic dashboard manager. Every 15 minutes, run a cron job to:
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1. Spawn sub-agents in parallel to fetch data from:
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- GitHub: stars, forks, open issues, commits (past 24h)
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- Twitter: mentions of "@username", sentiment analysis
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- Polymarket: volume for tracked markets
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- System: CPU, memory, disk usage via shell commands
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2. Each sub-agent writes results to the metrics database.
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3. Aggregate all results and format a dashboard:
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📊 **Dashboard Update** — [timestamp]
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**GitHub**
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- ⭐ Stars: [count] (+[change])
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- 🍴 Forks: [count]
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- 🐛 Open Issues: [count]
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- 💻 Commits (24h): [count]
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**Social Media**
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- 🐦 Twitter Mentions: [count]
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- 📈 Sentiment: [positive/negative/neutral]
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**Markets**
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- 📊 Polymarket Volume: $[amount]
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- 🔥 Trending: [market names]
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**System Health**
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- 💻 CPU: [usage]%
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- 🧠 Memory: [usage]%
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- 💾 Disk: [usage]%
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4. Post to Discord #dashboard.
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5. Check alert conditions:
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- If GitHub stars change > 50 in 1 hour → ping me
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- If system CPU > 90% → alert
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- If negative sentiment spike on Twitter → notify
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Store all metrics in the database for historical analysis.
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```
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4. Optional: Use Canvas to render an HTML dashboard with charts and graphs.
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5. Query historical data: "Show me GitHub star growth over the past 30 days."
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## Related Links
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- [Parallel Processing with Sub-agents](https://docs.openclaw.ai/subagents)
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- [Dashboard Design Principles](https://www.nngroup.com/articles/dashboard-design/)
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