windmill-integration-with-database-and-slack
Sub-skill of windmill: Integration with Database and Slack.
Best use case
windmill-integration-with-database-and-slack is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of windmill: Integration with Database and Slack.
Teams using windmill-integration-with-database-and-slack should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/integration-with-database-and-slack/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How windmill-integration-with-database-and-slack Compares
| Feature / Agent | windmill-integration-with-database-and-slack | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of windmill: Integration with Database and Slack.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Integration with Database and Slack
## Integration with Database and Slack
```python
# scripts/monitoring/database_health_check.py
"""
Monitor database health and alert on issues.
"""
import wmill
from datetime import datetime
import psycopg2
def main(
check_connections: bool = True,
check_slow_queries: bool = True,
slow_query_threshold_ms: int = 5000,
alert_channel: str = "#database-alerts",
):
"""
Run database health checks and alert on issues.
Args:
check_connections: Check connection pool status
check_slow_queries: Check for slow running queries
slow_query_threshold_ms: Threshold for slow query alerts
alert_channel: Slack channel for alerts
Returns:
Health check results
"""
db = wmill.get_resource("u/admin/production_db")
slack = wmill.get_resource("u/admin/slack_webhook")
results = {
"timestamp": datetime.now().isoformat(),
"checks": {},
"alerts": []
}
conn = psycopg2.connect(**db)
try:
with conn.cursor() as cur:
# Check active connections
if check_connections:
cur.execute("""
SELECT
count(*) as total,
count(*) FILTER (WHERE state = 'active') as active,
count(*) FILTER (WHERE state = 'idle') as idle,
count(*) FILTER (WHERE state = 'idle in transaction') as idle_in_txn
FROM pg_stat_activity
WHERE datname = current_database()
""")
conn_stats = cur.fetchone()
results["checks"]["connections"] = {
"total": conn_stats[0],
"active": conn_stats[1],
"idle": conn_stats[2],
"idle_in_transaction": conn_stats[3]
}
# Alert if too many connections
if conn_stats[0] > 80:
results["alerts"].append({
"type": "high_connections",
"message": f"High connection count: {conn_stats[0]}/100",
"severity": "warning"
})
# Check slow queries
if check_slow_queries:
cur.execute("""
SELECT
pid,
now() - pg_stat_activity.query_start AS duration,
query,
state
FROM pg_stat_activity
WHERE (now() - pg_stat_activity.query_start) > interval '%s milliseconds'
AND state != 'idle'
AND query NOT LIKE '%%pg_stat_activity%%'
""", (slow_query_threshold_ms,))
slow_queries = cur.fetchall()
results["checks"]["slow_queries"] = {
"count": len(slow_queries),
"threshold_ms": slow_query_threshold_ms,
"queries": [
{
"pid": q[0],
"duration": str(q[1]),
"query": q[2][:200],
"state": q[3]
}
for q in slow_queries[:5]
]
}
if slow_queries:
results["alerts"].append({
"type": "slow_queries",
"message": f"Found {len(slow_queries)} slow queries",
"severity": "warning"
})
finally:
conn.close()
# Send Slack alerts
if results["alerts"]:
send_slack_alert(slack, alert_channel, results)
return results
def send_slack_alert(slack, channel, results):
"""Send health check alerts to Slack."""
import requests
alert_texts = [
f"*{a['severity'].upper()}*: {a['message']}"
for a in results["alerts"]
]
requests.post(slack["url"], json={
"channel": channel,
"blocks": [
{
"type": "header",
"text": {
"type": "plain_text",
"text": "Database Health Alert"
}
},
{
"type": "section",
"text": {
"type": "mrkdwn",
"text": "\n".join(alert_texts)
}
},
{
"type": "context",
"elements": [
{
"type": "mrkdwn",
"text": f"Timestamp: {results['timestamp']}"
}
]
}
]
})
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