القائمة
Build interactive HTML dashboard artifacts with live database queries via the postMessage bridge. Includes a copy-paste helper function, workflow steps, and Chart.js integration patterns.
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استنادا إلى تصنيف SOC المهني
| name | live-dashboard |
| description | Build interactive HTML dashboard artifacts with live database queries via the postMessage bridge. Includes a copy-paste helper function, workflow steps, and Chart.js integration patterns. |
| roles | ["guide","conductor","reviewer","worker"] |
Build self-contained HTML dashboards that query the user's databases in real time through the System2 postMessage bridge.
Copy this helper into every dashboard. It wraps the raw postMessage protocol into a Promise-based API. Do not modify the field names (type, requestId, sql, database): the bridge matches on exact strings.
function queryDatabase(sql, database) {
return new Promise((resolve, reject) => {
const requestId = crypto.randomUUID();
function handler(event) {
const msg = event.data;
if (msg.requestId !== requestId) return;
if (msg.type === 'system2:query_result') {
window.removeEventListener('message', handler);
resolve(msg.rows);
} else if (msg.type === 'system2:query_error') {
window.removeEventListener('message', handler);
reject(new Error(msg.error));
}
}
window.addEventListener('message', handler);
window.parent.postMessage({
type: 'system2:query',
requestId,
sql,
...(database ? { database } : {})
}, '*');
});
}
Usage:
// Query the user's analytical database
const rows = await queryDatabase('SELECT * FROM sales LIMIT 100', 'analytics');
// Query app.db (System2 metadata)
const projects = await queryDatabase('SELECT * FROM project');
Identify the database. Check infrastructure.md for the database name configured under [databases.<name>] in config.toml. Pass this name as the database argument.
Explore the schema. Query information_schema or equivalent to discover tables and columns before writing the dashboard SQL. For PostgreSQL: SELECT table_schema, table_name, column_name, data_type FROM information_schema.columns WHERE table_schema NOT IN ('pg_catalog', 'information_schema') ORDER BY table_schema, table_name, ordinal_position. For SQLite: SELECT name, sql FROM sqlite_master WHERE type='table'.
Write the HTML file. A single self-contained .html file with inline CSS and JS. Structure:
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script> <!-- if needed -->
<style>/* all styles inline */</style>
</head>
<body>
<!-- controls and chart containers -->
<script>
// 1. queryDatabase helper (copy from above)
// 2. DOM references
// 3. Init: populate dropdowns/filters
// 4. Render function
// 5. Event listeners
</script>
</body>
</html>
Handle loading and errors. Show a loading indicator while queries run. Display error messages in the UI rather than silently failing. Disable controls during data fetches to prevent race conditions.
Register and show the artifact. Use write to save the file to the project's artifact directory, then show_artifact to open it in the viewer.
SELECT, WITH ... SELECT (CTEs), and EXPLAIN are allowed. The server rejects all mutations.max_rows (default 10,000). Use LIMIT for large tables.query_timeout seconds (default 30). Add LIMIT or filter clauses to keep queries fast.Load from CDN: https://cdn.jsdelivr.net/npm/chart.js
let chart = null;
function renderChart(labels, values, type = 'bar') {
const ctx = document.getElementById('myChart').getContext('2d');
if (chart) chart.destroy();
chart = new Chart(ctx, {
type,
data: {
labels,
datasets: [{ label: 'Values', data: values }]
},
options: {
responsive: true,
maintainAspectRatio: false
}
});
}
Populate a dropdown from a query:
async function populateSelect(selectId, sql, valueField, labelField, database) {
const rows = await queryDatabase(sql, database);
const select = document.getElementById(selectId);
select.innerHTML = '';
for (const row of rows) {
const opt = document.createElement('option');
opt.value = row[valueField];
opt.textContent = row[labelField];
select.appendChild(opt);
}
}
Multiple init queries in parallel:
await Promise.all([
populateSelect('countrySelect', 'SELECT code, name FROM country ORDER BY name', 'code', 'name', 'analytics'),
populateSelect('yearSelect', 'SELECT DISTINCT year FROM data ORDER BY year DESC', 'year', 'year', 'analytics'),
]);
// All dropdowns ready, trigger initial render
fetchAndRender();
Before calling show_artifact:
queryDatabase helper uses exact field names (type, requestId, sql, database)[databases.<name>] entry in the user's configUse when editing `~/.system2/config.toml` — adding or modifying a database connection, tuning per-agent overrides, or changing operational defaults. Does NOT cover `~/.system2/auth/.auth.toml` (managed by `system2 config`).
Run on first launch (when ~/.system2/knowledge/infrastructure.md is still the template) or whenever the user explicitly asks to re-onboard. Greets the user, learns about them, detects the system, installs and configures the data stack (database, orchestrator, Python environments), scaffolds the pipeline repository, and captures interaction preferences.
Use when building, debugging, deploying, or testing data pipelines with Prefect v3. Trigger on any code importing prefect, prefect YAML config, or user mentioning Prefect flows/tasks/deployments/workers.
Run before declaring project work complete. A self-audit checklist to honestly assess whether the deliverables actually meet the requirements before requesting final review or reporting completion to the Guide.
Run when delegating complex work to a new project. Gathers preliminary requirements with the user, creates the project in app.db, spawns a Conductor and Reviewer, introduces them to each other, updates the user, and schedules a follow-up reminder so a silent Conductor is noticed.
Use when building, debugging, scheduling, or testing data pipelines with Apache Airflow v3. Trigger on any code importing airflow, DAG definitions, operator usage, or user mentioning DAGs/tasks/operators/sensors/scheduling.