Agent skill · data analytics · borghei
cycle-time-analyzer
Flow metrics analyzer (lead time, cycle time, throughput, WIP, aging WIP) for sprint and team health, with cumulative flow diagrams.
Why this skill is useful
Adds specific commands for calculating and visualizing Kanban flow metrics that are not commonly known or documented.
What it needs
Requires python installed locally. About 4k tokens when loaded. Last updated 2026-07-21. 462 stars on the source repository.
What this skill does
Cycle Time Analyzer (Flow Metrics) Overview Compute and visualize the four core Kanban flow metrics -- lead time, cycle time, throughput, and work-in-progress -- from issue history data exported from Jira, Linear, GitHub Projects, or any tracker that records status transitions. The output is a dashboard suitable for sprint retrospectives, executive reporting, and bottleneck analysis, plus a Mermaid cumulative flow diagram that visualizes work accumulation over time. Flow metrics are the most useful diagnostic for team and process health, far more so than velocity or story points. Daniel Vacanti's work (Actionable Agile Metrics for Predictability, 2015) shows that predictability and throughput are governed by Little's Law (Throughput = WIP / Cycle Time), and that the most reliable way to improve delivery is to lower WIP and stabilize cycle time -- not to estimate harder. This skill also reports aging WIP (in-flight work older than the team's 85th-percentile cycle time -- the items most at risk) and supports the shared --format schema (json, markdown, mermaid, confluence, notion, linear). Core Capabilities Four flow metrics — lead time, cycle time (as a distribution, never an average), throughput, and WIP, tied together by Little's Law. Aging WIP — flags in-flight items older than the 85th-percentile cycle time as at-risk; the most actionable daily metric. Cumulative flow diagram — Mermaid CFD for retrospectives and exec reports. Per-type filtering & trends — bug/feature/spike breakdowns over rolling 6-8 week windows across all six output formats. When to Use Sprint retrospective -- A team wants data-driven discussion of why some sprints feel slow. Bottleneck investigation -- Throughput has fallen and the team needs to identify the constraining step. Quarterly delivery review -- Leadership wants a real picture of delivery performance beyond story-point velocity. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills borghei/cycle-time-analyzer