qbr-generatorlisted

# QBR Generator Transforms raw account data exports into a quarterly business review package: health narrative, spend trend analysis, adoption story, risk flags, and a slide-by-slide deck outline. ## Inputs - `orders.csv`: order_id, date, category, amount, fulfillment_status - `support.csv`: ticket_id, opened, closed, severity, category - `adoption.csv` (optional): feature, monthly_active_users, month - Account context: contract value, renewal date, key stakeholders, prior-quarter commitments Sample synthetic inputs live in `references/sample_data/`. ## Workflow 1. Run `scripts/aggregate.py` to compute quarter-over-quarter spend, category mix shift, order velocity, ticket volume and mean-time-to-resolution. 2. Score account health using the rubric in `references/health_rubric.md` (spend trend 40%, adoption 30%, support burden 20%, engagement 10%). 3. Write the narrative in this order: headline metric, what changed this quarter, why it changed, risk or expansion signal, recommended next commitment. 4. Produce a deck outline: title slide, executive summary, spend and adoption trends, support review, roadmap alignment, proposed next-quarter commitments. 5. Flag every claim in the narrative against a computed number. No unverifiable statements in customer-facing output. ## Output format Markdown package with three sections: `## Executive Summary` (under 150 words), `## Health Analysis` (metrics table plus narrative), `## Deck Outline` (one line per slide with the single n