What problem does it solve? Manually compiling daily work summaries from scattered sources like Git commits, emails, and todo lists is time-consuming and error-prone. This Skill automates multi-source data collection and report generation, delivering structured Markdown reports with optional AI-powered analysis. ## Core Features & Use Cases - Multi-Source Data Collection: Aggregates Git commit history via git log, NetEase email statistics via IMAP, memory files, and todo.md task states into unified datasets. - AI-Powered Analysis: Generates intelligent summaries, tomorrow's plan suggestions, and 7-day work pattern analysis (peak hours, commit frequency) using an LLM (glm-4.7). - Multiple Report Types: Produces daily, weekly, and monthly reports with trend comparisons, productivity scores, and code change statistics, saved as Markdown files. - Use Case: A developer ends their workday and asks the agent to generate today's report; the Skill collects 5 Git commits, 3 completed tasks, and 12 emails, then outputs a formatted report with an AI summary and tomorrow's plan. ## Quick Start Ask the agent to generate today's daily report, and it will run the report script, collect your Git, email, memory, and todo data, then display the full Markdown report.
