# Retro Analysis

> Analyses sprint delivery data and produces a structured retrospective brief. Use when asked to run a retrospective, analyse sprint data, prepare a retro brief, or turn sprint metrics into discussion prompts. Produces a data-grounded retrospective brief with completion stats, pattern analysis, Start/Stop/Continue prompts, and one concrete experiment for next sprint.

- Skill: `mohitagw15856/retro-analysis` (Agent Skill, multi-file: 4 files)
- Install (CLI): `npx skillmds add mohitagw15856/retro-analysis`
- Raw SKILL.md: https://api.skillmd.com/api/skills/mohitagw15856/retro-analysis/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: Mohit Aggarwal (https://skillmd.com/u/mohitagw15856)
- Updated: 2026-09-07
- Page: https://skillmd.com/skills/mohitagw15856/retro-analysis

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# 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]

## Deeper Materials

This skill ships with support files — use them when they are available:

- **`references/root-cause-vs-symptom.md`** — Retros That Change Things: Root Causes vs Symptoms. Apply it while producing the output; it carries the calibration and judgment calls the method summary above compresses.
- **`templates/retro-board.md`** — a fill-in version of the deliverable with the quality gates inline. Offer it when the user wants to work the document themselves rather than have it generated.

## Scoring Rubric (0–40)

Score any output of this skill before handing it over; 32+ is ship-quality.

| Dimension | 0 | 5 | 10 |
|---|---|---|---|
| **Data grounding** | Numbers missing or wrong; observations are opinions with no traceable source | Core rates computed correctly, but observations only restate the numbers without pattern analysis (ticket types, historical comparison) | Every observation traces to a computed figure, carry-over is broken down by type/cause, and velocity is compared against the historical trend, not just the average |
| **Blamelessness** | Brief names or implies individuals/disciplines as the cause ("QA missed them") | Neutral wording, but framing still points at effort or diligence rather than systemic conditions | Failure modes are reframed as process/coverage/scheduling patterns the data actually supports — a defensive reader would find nothing aimed at them |
| **Prompt specificity** | Start/Stop/Continue are recycled generic categories ("communicate better") | Prompts reference this sprint but stay at category level — no numbers, no named behaviour | Each prompt is welded to this sprint's data, names one specific behaviour, and is phrased to open discussion rather than dictate the answer |
| **Experiment quality** | No experiment, or a multi-quarter initiative dressed as one | One concrete change, but success is unmeasurable or can't be evaluated at the next retro | One process change testable within a single sprint, with explicit success metrics and a stated cost-if-wrong, checkable at the next retro |

## 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