Analyze git commit history and code quality metrics to generate engineering retrospectives.
npx skills add https://github.com/ajsai47/holyclaude --skill retro-ajsai47
Please help me install this Agent Skill. Skill: retro Source: https://github.com/ajsai47/holyclaude/tree/main/skills/team/retro Command: npx skills add https://github.com/ajsai47/holyclaude --skill retro-ajsai47
Engineering teams lack structured visibility into shipping velocity, code quality trends, and individual contribution patterns across sprints. Ad-hoc retrospectives miss critical data and fail to track improvement over time.
Use the retro skill to analyze the last two weeks of engineering work and generate a team retrospective report with per-person praise and growth areas.
High-intent search queries and answers about installing and using this skill.
Generate engineering retrospectives from git history by parsing commit logs, work patterns, and code quality metrics over a time window. The analysis produces per-contributor praise and growth areas alongside team velocity trends for sprint reviews.
Track sprint velocity and code quality trends by comparing current metrics against prior periods. This cross-session trend tracking spots regressions or improvements in test coverage and code health over time windows ranging from 24 hours to 30 days.
Per-contributor performance analysis breaks down git contributions per person, measuring commits and LOC changes. It identifies specific praise for strengths and growth areas for each teammate, providing structured visibility into individual contribution patterns.
Git repository access is required to analyze commit metrics, while gstack configuration is optional for telemetry. The analysis works with standard git logs but can leverage gstack for enhanced engineering telemetry data.
Global mode enables cross-project engineering metrics analysis, while standard mode focuses on a single repository. Both modes measure commit velocity and code quality over configurable time windows from 24 hours to 30 days.
Ad-hoc retrospectives miss critical engineering data because they lack structured visibility into shipping velocity and code quality trends across sprints. Automated git history analysis captures commit patterns and contribution metrics that manual reviews fail to track.
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