> clari-webhooks-events
Monitor Clari forecast changes using export job polling and change detection. Use when tracking forecast submission changes, building alerts for significant forecast movements, or syncing Clari data in near-real-time. Trigger with phrases like "clari webhooks", "clari notifications", "clari forecast alerts", "clari change detection".
curl "https://skillshub.wtf/jeremylongshore/claude-code-plugins-plus-skills/clari-webhooks-events?format=md"Clari Webhooks & Events
Overview
Clari does not provide real-time webhooks. Instead, build change detection by comparing periodic exports. This skill covers scheduled export diffing, Slack alerts for forecast movements, and Copilot webhook integration.
Instructions
Step 1: Forecast Change Detection Pipeline
# forecast_monitor.py
import json
from pathlib import Path
from datetime import datetime
def detect_changes(
current: list[dict],
previous: list[dict],
threshold_pct: float = 10.0,
) -> list[dict]:
prev_map = {e["ownerEmail"]: e for e in previous}
changes = []
for entry in current:
prev = prev_map.get(entry["ownerEmail"])
if not prev:
continue
prev_fc = prev["forecastAmount"]
curr_fc = entry["forecastAmount"]
if prev_fc == 0:
continue
change_pct = ((curr_fc - prev_fc) / prev_fc) * 100
if abs(change_pct) >= threshold_pct:
changes.append({
"rep": entry["ownerName"],
"previous": prev_fc,
"current": curr_fc,
"change_pct": round(change_pct, 1),
"direction": "increased" if change_pct > 0 else "decreased",
"detected_at": datetime.utcnow().isoformat(),
})
return sorted(changes, key=lambda x: abs(x["change_pct"]), reverse=True)
def save_snapshot(entries: list[dict], path: str = "data/latest.json"):
Path(path).parent.mkdir(exist_ok=True)
with open(path, "w") as f:
json.dump(entries, f)
def load_snapshot(path: str = "data/latest.json") -> list[dict]:
try:
with open(path) as f:
return json.load(f)
except FileNotFoundError:
return []
Step 2: Slack Alert for Forecast Changes
import requests
def send_forecast_alert(changes: list[dict], slack_webhook: str):
if not changes:
return
blocks = [f"*Clari Forecast Changes Detected*\n"]
for c in changes[:10]:
emoji = ":chart_with_upwards_trend:" if c["direction"] == "increased" else ":chart_with_downwards_trend:"
blocks.append(
f"{emoji} *{c['rep']}*: ${c['previous']:,.0f} -> ${c['current']:,.0f} "
f"({c['change_pct']:+.1f}%)"
)
requests.post(slack_webhook, json={"text": "\n".join(blocks)})
Step 3: Scheduled Monitor (Cron)
#!/bin/bash
# Run every 4 hours: 0 */4 * * * /path/to/clari-monitor.sh
cd /opt/clari-integration
python3 -c "
from clari_client import ClariClient
from forecast_monitor import detect_changes, save_snapshot, load_snapshot, send_forecast_alert
import os
client = ClariClient()
data = client.export_and_download('company_forecast', '2026_Q1')
current = data.get('entries', [])
previous = load_snapshot()
changes = detect_changes(current, previous)
if changes:
send_forecast_alert(changes, os.environ['SLACK_WEBHOOK_URL'])
print(f'Detected {len(changes)} changes')
save_snapshot(current)
"
Step 4: Copilot Webhook (Conversation Intelligence)
The Clari Copilot API supports real-time webhooks for call events:
# Register webhook with Copilot API
curl -X POST https://api.copilot.clari.com/v1/webhooks \
-H "Authorization: Bearer ${COPILOT_ACCESS_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"url": "https://your-app.com/webhooks/clari-copilot",
"events": ["call.completed", "call.analyzed"]
}'
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| False change alerts | Data timing differences | Increase threshold to 15% |
| Snapshot file missing | First run | Initialize with empty list |
| Slack post fails | Bad webhook URL | Test URL with curl |
Resources
Next Steps
For performance optimization, see clari-performance-tuning.
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