customer-snapshot

What problem does it solve?

Solutions Engineers need a single, screen-shareable view that aggregates a customer's Jira issues, Slack sentiment, Asana actions, and BigQuery usage so they can prepare for calls, QBRs, and escalations without jumping between tools.

Core Features & Use Cases

• Deterministic two-stage pipeline: assemble data (assemble.py) and compose folder-based dashboards (compose.py) into customers/<name>/dashboard/.
• Multi-source aggregation: pulls Jira issues with comments, optional Slack sentiment, Asana actions, and BigQuery usage; normalizes components and parent epics and computes trending/velocity metrics.
• Professional, shareable output: index.html shell, data.js INTELLIGENCE_DATA, modular panels/, lib/ (ECharts), and history snapshots with internal/external audience toggle.
• Graceful degradation and diagnostics: panels show empty states when sources are unavailable, and analytics transforms are stubbed with clear reasons.

Quick Start

Invoke the skill with a customer name, for example /customer-snapshot GResearch, to fetch sources, assemble INTELLIGENCE_DATA, and compose a dashboard folder you can open in a browser.