clari-core-workflow-a

name	clari-core-workflow-a
description	Build a Clari forecast export pipeline to your data warehouse. Use when exporting forecast calls, quota data, and CRM totals from Clari to Snowflake, BigQuery, or a local database. Trigger with phrases like "clari forecast export", "clari data pipeline", "clari to snowflake", "clari to bigquery", "export clari data".
allowed-tools	Read, Write, Edit, Bash(python3:*), Bash(curl:*), Grep
version	1.6.0
license	MIT
author	Jeremy Longshore <[e-mail]>
tags	["saas","revenue-intelligence","forecasting","clari"]
compatibility	Designed for Claude Code

Clari Core Workflow: Forecast Export Pipeline

Overview

Primary workflow: build an automated pipeline that exports forecast submissions, quota, adjustments, and CRM data from Clari to your data warehouse. Supports Snowflake, BigQuery, and PostgreSQL as targets.

Prerequisites

• Completed clari-install-auth and clari-sdk-patterns setup
• Target database or data warehouse with write access
• Python 3.10+ with requests and your DB driver

Instructions

Step 1: Define Export Configuration

# config.py
from dataclasses import dataclass

@dataclass
class ExportConfig:
    forecast_name: str          # From Clari forecast list
    time_periods: list[str]     # e.g., ["2026_Q1", "2025_Q4"]
    export_types: list[str] = None
    currency: str = "USD"
    include_historical: bool = True

    def __post_init__(self):
        if self.export_types is None:
            self.export_types = [
                "forecast",           # Submitted forecast call
                "forecast_updated",   # Updated forecast history
                "quota",              # Quota values
                "adjustment",         # Manager adjustments
                "crm_total",          
                ,         
            ]