What problem does it solve? Compiling weekly engineering status reports from GitHub releases, commits, and Jira issues is repetitive manual work. This Skill automates the entire pipeline: collecting data, computing delivery metrics (velocity, lead time, cycle time, WIP aging, rework), generating AI-written summaries in multiple formats, and publishing results to Notion and Discord. ## Core Features & Use Cases - Multi-source data collection: Fetches weekly releases and commits from multiple GitHub repositories and branches, plus Jira issues with full status-change history via the Jira REST API. - Engineering metrics: Computes weekly throughput, lead time p50/p85, cycle time, queue time, flow efficiency, deploy lag, WIP aging, and rework breakdown, rendered as ASCII charts for Discord. - AI-generated summaries: Produces FAQ (sales/support and end-user), CEO executive summary, Discord message, email, RAG-indexable text, and a structured Notion page payload via an LLM. - Automated distribution: Creates a Notion database page per release and posts the report to a Discord channel, optionally inside a weekly thread. - Use Case: A tech lead runs the pipeline every Friday to publish a weekly report thread in Discord with velocity charts and a Notion changelog page, without writing anything by hand. ## Quick Start Set the required environment variables for GitHub, Jira, Notion, and Discord, then run python skills/github-weekly-summary/scripts/main.py to generate and publish the weekly report.