Analyze Git history to generate per-author retrospective reports.
npx skills add https://github.com/vibrationalforce/Echoelmusic --skill retro-vibrationalforce
Please help me install this Agent Skill. Skill: retro Source: https://github.com/vibrationalforce/Echoelmusic/tree/main/.claude/skills/gstack/retro Command: npx skills add https://github.com/vibrationalforce/Echoelmusic --skill retro-vibrationalforce
Weekly engineering retrospectives are often manual, inconsistent, and hard to compare over time. This Skill automates the collection and synthesis of commit history, work patterns, and code quality metrics to deliver a repeatable, team-aware retrospective that highlights praise, growth opportunities, and actionable insights.
Run the retro command for your desired window, for example '/retro 7d' to generate a weekly snapshot.
High-intent search queries and answers about installing and using this skill.
Automate engineering retrospectives by analyzing a repository's Git history to generate a team-aware report with per-author praise, growth opportunities, and actionable focus insights. Run a command like '/retro 7d' to produce a weekly snapshot without manual data collection.
Yes, generating per-person code quality metrics from commit data produces individual praise and growth opportunities. The retrospective analyzes Git contributions to create per-author breakdowns, highlighting specific engineering patterns and work signals for each team member.
Compare engineering sprint metrics across different time windows using configurable parameters like 7d, 14d, or 30d. Compare mode surfaces trend data over time, allowing you to contrast shipping velocity, code quality, and focus areas between historical snapshots.
The best way to run a team-aware retrospective for a multi-week sprint is applying the retrospective tool to a 14d or 30d window. This analyzes the extended Git history to produce comprehensive trend data, test signals, and per-author breakdowns for the entire period.
No, the automated retrospective requires no external dependencies or CI integrations to function. It operates independently using scripts and references to collect Git data and generate structured output directly from the repository's commit history.
Actionable insights in an automated Git retrospective report include focus areas, shipping velocity, and code quality signals. The structured output provides per-author breakdowns, trend data, and test signals to guide team improvements and highlight growth opportunities.
geoffreywooGenerates weekly engineering retrospective reports from Git commit history and per-author statistics.
devmuslimTrack stakeholder satisfaction KPIs for product releases via surveys and issue tracking.
whd4Aggregates code quality metrics from multiple tools into a 0-10 score with trends.
cegit27Analyze git commit history to generate weekly retrospective reports.
