Export KPI totals by program and client from ReturnPro financial data.
npx skills add https://github.com/clenisa/optimal-cli --skill export-kpis
Please help me install this Agent Skill. Skill: export-kpis Source: https://github.com/clenisa/optimal-cli/tree/main/skills/export-kpis Command: npx skills add https://github.com/clenisa/optimal-cli --skill export-kpis
This Skill automates exporting KPI totals aggregated by program, client, and month from ReturnPro financial data to remove manual SQL querying and table assembly for ad-hoc analysis, reporting, and validation.
Run the export-kpis command to fetch KPI totals for the latest three months and return a markdown table.
High-intent search queries and answers about installing and using this skill.
Export KPI totals by program and client from Supabase by querying the stg_financials_raw table through the get_kpi_totals_by_program_client RPC, which flattens aggregated financial data into consumable rows for stakeholder reporting and validation.
Filter financial KPI exports by applying partial program name matches against the dim_master_program table, allowing flexible program selection without requiring exact identifiers when generating monthly KPI reports.
Export KPI totals from ReturnPro by configuring the RETURNPRO_SUPABASE_URL and RETURNPRO_SUPABASE_SERVICE_KEY environment variables, which authenticate access to the stg_financials_raw table and the get_kpi_totals_by_program_client RPC.
The KPI export tool supports CSV format for spreadsheet reconciliation by formatting flattened RPC query results into downloadable files, alongside markdown table output for direct stakeholder presentation.
Month-over-month KPI comparisons resolve months by defaulting to the three most recent months containing financial data in the stg_financials_raw table, ensuring empty periods are skipped automatically.
Automate monthly KPI reporting across multiple programs by replacing manual SQL with the export-kpis Skill, which calls the get_kpi_totals_by_program_client RPC to aggregate and flatten data by month, program, and client into ready-to-use formats.
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