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Clari hello world

Skill jeremylongshore/claude-code-plugins-plus-skills/plugins/saas-packs/clari-pack/skills/clari-hello-world

'Export your first Clari forecast and pipeline snapshot.From its SKILL.md

Install
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill clari-hello-world

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SKILL.md

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Clari Hello World

Overview

First API calls against Clari: list available forecasts, export a forecast snapshot, and check export job status. The Clari Export API is the primary integration point for getting forecast, quota, and CRM data out of Clari.

Prerequisites

  • Completed clari-install-auth setup
  • CLARI_API_KEY environment variable set
  • At least one forecast configured in Clari

Instructions

Step 1: List Available Forecasts

curl -s -H "apikey: ${CLARI_API_KEY}" \
  https://api.clari.com/v4/export/forecast/list \
  | jq '.forecasts[] | {forecastName, forecastId, timePeriods}'

Step 2: Export a Forecast

import requests
import json
import os
import time

api_key = os.environ["CLARI_API_KEY"]
headers = {"apikey": api_key, "Content-Type": "text/plain"}

# Replace with your forecast name from Step 1
forecast_name = "company_forecast"

payload = json.dumps({
    "timePeriod": "2026_Q1",
    "typesToExport": [
        "forecast",
        "quota",
        "forecast_updated",
        "adjustment",
        "crm_total",
        "crm_closed"
    ],
    "currency": "USD",
    "schedule": "NONE",
    "includeHistorical": False,
    "exportFormat": "JSON"
})

response = requests.post(
    f"https://api.clari.com/v4/export/forecast/{forecast_name}",
    headers=headers,
    data=payload,
)
response.raise_for_status()

job = response.json()
print(f"Export job started: {job['jobId']}")
print(f"Status: {job['status']}")

Step 3: Check Export Job Status

# Poll for job completion
job_id = job["jobId"]

while True:
    status_resp = requests.get(
        f"https://api.clari.com/v4/export/jobs/{job_id}",
        headers={"apikey": api_key},
    )
    status = status_resp.json()

    if status["status"] == "COMPLETED":
        print(f"Export ready: {status['downloadUrl']}")
        break
    elif status["status"] == "FAILED":
        print(f"Export failed: {status.get('error', 'Unknown')}")
        break

    print(f"Status: {status['status']}... waiting 5s")
    time.sleep(5)

Step 4: Download and Parse Results

if status["status"] == "COMPLETED":
    download = requests.get(status["downloadUrl"])
    forecast_data = download.json()

    # Print summary
    for entry in forecast_data.get("entries", [])[:5]:
        print(f"  Rep: {entry.get('ownerName')}")
        print(f"  Forecast: ${entry.get('forecastAmount', 0):,.0f}")
        print(f"  Quota: ${entry.get('quotaAmount', 0):,.0f}")
        print()

Output

  • List of forecasts with IDs and time periods
  • Exported forecast data with rep-level calls
  • Quota, adjustments, and CRM totals

Error Handling

ErrorCauseSolution
401 UnauthorizedBad API keyRegenerate token in Clari settings
No forecasts listedWrong org or no forecasts configuredContact Clari admin
Job stays PENDINGLarge exportWait longer, check job status endpoint
404 on forecast nameName mismatchUse exact name from list endpoint

Resources

Next Steps

Proceed to clari-local-dev-loop for development workflow setup.

What ships with it

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Just SKILL.md. No reference files, no scripts.

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