retro-analysis
Retro-analysis generates a data-grounded retrospective brief from sprint metrics including completion rates, carry-over analysis, unplanned work, and velocity trends. Use this skill when a team needs to prepare for a retrospective meeting, transform raw sprint data into discussion prompts, or identify concrete process experiments. The output separates factual patterns from subjective interpretation, providing Start/Stop/Continue prompts tied to specific sprint behaviors and one measurable experiment for the next sprint.
git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills /tmp/retro-analysis && cp -r /tmp/retro-analysis/plugins/pm-delivery/skills/retro-analysis ~/.claude/skills/retro-analysisSKILL.md
# Retrospective Analysis Skill Generate a data-grounded retrospective brief that separates facts from feelings, so the team spends retro time on solutions rather than debating what happened. ## Required Inputs Ask the user for these if not provided: - **Sprint tickets: planned vs. completed** - **Carry-over tickets and reasons** (if known) - **Tickets reopened after closing** (quality signal) - **Any incidents or unplanned work** (scope creep signal) - **Sprint velocity vs. historical average** (trend context) ## Process 1. Calculate: completion rate, carry-over rate, unplanned work percentage 2. Identify patterns: which ticket types were most likely to carry over? Which caused blockers? 3. Note any process or communication breakdowns visible in the data 4. Prepare 3 "Start / Stop / Continue" prompts based on the data — not generic, specific to this sprint 5. Suggest 1 concrete experiment for the next sprint based on the biggest friction point 6. **Validate** — Confirm each prompt is specific to this sprint (not a recycled generic prompt), and that the recommended experiment is concrete and measurable ## Output Structure ### Sprint [Number] Retrospective Brief **By the Numbers:** - Planned: [n] tickets | Completed: [n] | Carry-over: [n] | Completion rate: [%] - Unplanned work: [n] tickets ([%] of capacity) - Velocity: [points] vs. [average] average **What the Data Suggests:** [2-3 observations grounded in the numbers above] **Discussion Prompts:** - Start: [specific prompt based on this sprint's data] - Stop: [specific prompt based on this sprint's data] - Continue: [specific prompt based on this sprint's data] **Suggested Experiment for Next Sprint:** [One concrete, testable process change — with a specific success metric] ## Quality Checks - [ ] Each Start/Stop/Continue prompt names a specific behaviour, not a vague category - [ ] The recommended experiment is testable in one sprint - [ ] Carry-over analysis identifies the ticket type or cause, not just the count - [ ] Data observations don't assign blame — they describe patterns - [ ] Velocity trend is mentioned in context (is this a one-off or a pattern?) ## Anti-Patterns - [ ] Do not assign blame to individuals in the retrospective brief — observations must describe patterns, not people - [ ] Do not produce Start/Stop/Continue prompts that are vague categories — each must name a specific behaviour - [ ] Do not recommend an experiment that cannot be completed within one sprint — small, testable experiments only - [ ] Do not treat carry-over tickets as a velocity problem without first identifying the root cause category - [ ] Do not run the same retrospective format every sprint — vary the format to prevent engagement fatigue
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