Agent skill · data analytics · borghei
sprint-retrospective
Data-driven sprint retrospectives from git history — velocity, cycle/lead time, contributor insights, and churn hotspots. Use to run a retrospective, analyze team velocity or throughput, or generate a retro report from commit history.
Why this skill is useful
Adds 4 executable Python scripts for analyzing sprint data and generating reports that aren't in public docs.
What it needs
Requires git, python installed locally. About 4k tokens when loaded. Last updated 2026-07-21. 462 stars on the source repository.
What this skill does
Sprint Retrospective Expert The agent acts as a data-driven retrospective facilitator that mines git history, PR metadata, and commit patterns to generate comprehensive sprint retrospective reports. It goes beyond simple commit counts — analyzing velocity trends, contributor work patterns, code health indicators, and team collaboration dynamics to surface actionable insights. Four stdlib Python tools (velocity, contributor, churn, report generator) chain into a single pipeline. Keywords: sprint retrospective, velocity analytics, contributor insights, code churn, work sessions, cycle time, lead time, throughput, burndown, team health, collaboration metrics, bus factor, refactor ratio, hotspot analysis, conventional commits, session detection, deep work, improvement tracking Core Capabilities Velocity analysis — throughput, cycle/lead time, deploy frequency, commit-type breakdown, work-session detection (deep/focused/micro) Contributor deep dive — per-person LOC, peak hours, specialization (frontend/backend/infra/docs/tests/data), consistency, collaboration Code quality trends — churn hotspots, oscillation, test-to-production ratio, refactor frequency, healthy-range indicators Team health — review coverage, bus factor / knowledge-silo detection, cross-boundary work Report generation & trend tracking — narrative markdown reports, sprint snapshots, sprint-over-sprint deltas, action-item carry-over When to Use Running a weekly (7d), standard sprint (14d), or monthly/PI (30d) retrospective Producing a data-dense retro report or executive sprint summary from git history Diagnosing velocity, cycle-time, or review-bottleneck trends across sprints Identifying churn hotspots, refactoring candidates, or bus-factor / knowledge-silo risks Tracking follow-through on action items from previous retros Automating retrospectives on a CI/CD schedule Clarify First Before generating the retro report, confirm these inputs. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills borghei/sprint-retrospective