retro_skill

This skill analyzes completed sprints to reveal velocity trends, scope changes, and patterns for actionable retro improvements.
  • Shell

0

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

3 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill alienfast/claude --skill retro

  • SKILL.md3.6 KB

Overview

This skill analyzes completed Linear cycles to generate actionable retrospective insights. It identifies velocity trends, scope creep, blockers, and workload distribution to improve future sprint planning. The output is concise, data-driven, and structured for quick discussion and follow-up.

How this skill works

The skill gathers cycle metadata and issue lists, compares planned versus completed points and issue counts, and detects mid-cycle scope changes. It highlights blocked work, estimation gaps, and per-assignee load, then summarizes trends across recent cycles and produces prioritized action items and discussion prompts.

When to use it

  • After a sprint or cycle has ended and you need a retrospective summary
  • When preparing materials for a retrospective meeting
  • To validate trends before adjusting planning or estimation practices
  • When investigating repeated blockers or delivery bottlenecks
  • To quantify scope creep and inform scope freeze policies

Best practices

  • Be data-driven: base every insight on cycle metrics and issue history
  • Focus on process-level improvements, not individual performance
  • Produce actionable recommendations with clear owners and due dates
  • Compare multiple recent cycles to surface true trends
  • Use discussion prompts to turn analysis into team decisions

Example use cases

  • Generate a one-page retrospective summary for Cycle 23, including velocity, scope changes, and action items
  • Detect recurring blocked issues and estimate average time lost to blockers across three cycles
  • Measure scope creep percentage and identify issues added mid-cycle to inform scope freeze rules
  • Spot estimation inaccuracies by comparing planned vs actual points per issue and highlight high-variance items
  • Review workload distribution to reveal bottlenecks and rebalance future assignments

FAQ

Cycle identifiers or a count of recent cycles and team context to fetch issue lists, estimates, and timeline events.

How are scope creep and blockers measured?

Scope creep is percentage of points or issues added mid-cycle; blockers are derived from dependency/blocked flags and time-in-blocked-state metrics.

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