retro

name	retro
version	2.0.0
description	Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware: breaks down per-person contributions with praise and growth areas.
allowed-tools	["Bash","Read","Write","Glob","AskUserQuestion"]

Integration: This skill uses gstack for update checking, session tracking, and the "Boil the Lake" retrospective principle. If gstack is not installed, those features gracefully degrade.

Preamble (run first)

_UPD=$(~/.claude/skills/gstack/bin/gstack-update-check 2>/dev/null || .claude/skills/gstack/bin/gstack-update-check 2>/dev/null || true)
[ -n "$_UPD" ] && echo "$_UPD" || true
mkdir -p ~/.gstack/sessions
touch ~/.gstack/sessions/"$PPID"
_SESSIONS=$(find ~/.gstack/sessions -mmin -120 -type f 2>/dev/null | wc -l | tr -d ' ')
find ~/.gstack/sessions -mmin +120 -type f -delete 2>/dev/null || true
_CONTRIB=$(~/.claude/skills/gstack/bin/gstack-config get gstack_contributor 2>/dev/null || true)
_BRANCH=$(git branch --show-current 2>/dev/null || echo "unknown")
echo "BRANCH: $_BRANCH"
_LAKE_SEEN=$([ -f ~/.gstack/.completeness-intro-seen ] && echo "yes" || echo "no")
echo "LAKE_INTRO: $_LAKE_SEEN"

If output shows UPGRADE_AVAILABLE <old> <new>: read ~/.claude/skills/gstack/gstack-upgrade/SKILL.md and follow the "Inline upgrade flow" (auto-upgrade if configured, otherwise AskUserQuestion with 4 options, write snooze state if declined). If JUST_UPGRADED <from> <to>: tell user "Running gstack v{to} (just updated!)" and continue.

If LAKE_INTRO is no: Before continuing, introduce the Completeness Principle. Tell the user: "gstack follows the Boil the Lake principle — always do the complete thing when AI makes the marginal cost near-zero. Read more: https://garryslist.org/posts/boil-the-ocean" Then offer to open the essay in their default browser:

open https://garryslist.org/posts/boil-the-ocean
touch ~/.gstack/.completeness-intro-seen

Only run open if the user says yes. Always run touch to mark as seen. This only happens once.

AskUserQuestion Format

ALWAYS follow this structure for every AskUserQuestion call:

1. Re-ground: State the project, the current branch (use the _BRANCH value printed by the preamble — NOT any branch from conversation history or gitStatus), and the current plan/task. (1-2 sentences)
2. Simplify: Explain the problem in plain English a smart 16-year-old could follow. No raw function names, no internal jargon, no implementation details. Use concrete examples and analogies. Say what it DOES, not what it's called.
3. Recommend: RECOMMENDATION: Choose [X] because [one-line reason] — always prefer the complete option over shortcuts (see Completeness Principle). Include Completeness: X/10 for each option. Calibration: 10 = complete implementation (all edge cases, full coverage), 7 = covers happy path but skips some edges, 3 = shortcut that defers significant work. If both options are 8+, pick the higher; if one is ≤5, flag it.
4. Options: Lettered options: A) ... B) ... C) ... — when an option involves effort, show both scales: (human: ~X / CC: ~Y)

Assume the user hasn't looked at this window in 20 minutes and doesn't have the code open. If you'd need to read the source to understand your own explanation, it's too complex.

Per-skill instructions may add additional formatting rules on top of this baseline.

Completeness Principle — Boil the Lake

AI-assisted coding makes the marginal cost of completeness near-zero. When you present options:

• If Option A is the complete implementation (full parity, all edge cases, 100% coverage) and Option B is a shortcut that saves modest effort — always recommend A. The delta between 80 lines and 150 lines is meaningless with CC+gstack. "Good enough" is the wrong instinct when "complete" costs minutes more.
• Lake vs. ocean: A "lake" is boilable — 100% test coverage for a module, full feature implementation, handling all edge cases, complete error paths. An "ocean" is not — rewriting an entire system from scratch, adding features to dependencies you don't control, multi-quarter platform migrations. Recommend boiling lakes. Flag oceans as out of scope.
• When estimating effort, always show both scales: human team time and CC+gstack time. The compression ratio varies by task type — use this reference:

Task type	Human team	CC+gstack	Compression
Boilerplate / scaffolding	2 days	15 min	~100x
Test writing	1 day	15 min	~50x
Feature implementation	1 week	30 min	~30x
Bug fix + regression test	4 hours	15 min	~20x
Architecture / design	2 days	4 hours	~5x
Research / exploration	1 day	3 hours	~3x

• This principle applies to test coverage, error handling, documentation, edge cases, and feature completeness. Don't skip the last 10% to "save time" — with AI, that 10% costs seconds.

Anti-patterns — DON'T do this:

• BAD: "Choose B — it covers 90% of the value with less code." (If A is only 70 lines more, choose A.)
• BAD: "We can skip edge case handling to save time." (Edge case handling costs minutes with CC.)
• BAD: "Let's defer test coverage to a follow-up PR." (Tests are the cheapest lake to boil.)
• BAD: Quoting only human-team effort: "This would take 2 weeks." (Say: "2 weeks human / ~1 hour CC.")

Contributor Mode

If _CONTRIB is true: you are in contributor mode. You're a gstack user who also helps make it better.

At the end of each major workflow step (not after every single command), reflect on the gstack tooling you used. Rate your experience 0 to 10. If it wasn't a 10, think about why. If there is an obvious, actionable bug OR an insightful, interesting thing that could have been done better by gstack code or skill markdown — file a field report. Maybe our contributor will help make us better!

Calibration — this is the bar: For example, $B js "await fetch(...)" used to fail with SyntaxError: await is only valid in async functions because gstack didn't wrap expressions in async context. Small, but the input was reasonable and gstack should have handled it — that's the kind of thing worth filing. Things less consequential than this, ignore.

NOT worth filing: user's app bugs, network errors to user's URL, auth failures on user's site, user's own JS logic bugs.

To file: write ~/.gstack/contributor-logs/{slug}.md with all sections below (do not truncate — include every section through the Date/Version footer):

# {Title}

Hey gstack team — ran into this while using /{skill-name}:

**What I was trying to do:** {what the user/agent was attempting}
**What happened instead:** {what actually happened}
**My rating:** {0-10} — {one sentence on why it wasn't a 10}

## Steps to reproduce
1. {step}

## Raw output

{paste the actual error or unexpected output here}

## What would make this a 10
{one sentence: what gstack should have done differently}

**Date:** {YYYY-MM-DD} | **Version:** {gstack version} | **Skill:** /{skill}

Slug: lowercase, hyphens, max 60 chars (e.g. browse-js-no-await). Skip if file already exists. Max 3 reports per session. File inline and continue — don't stop the workflow. Tell user: "Filed gstack field report: {title}"

Detect default branch

Before gathering data, detect the repo's default branch name: gh repo view --json defaultBranchRef -q .defaultBranchRef.name

If this fails, fall back to main. Use the detected name wherever the instructions say origin/<default> below.

---

/retro — Weekly Engineering Retrospective

Generates a comprehensive engineering retrospective analyzing commit history, work patterns, and code quality metrics. Team-aware: identifies the user running the command, then analyzes every contributor with per-person praise and growth opportunities. Designed for a senior IC/CTO-level builder using Claude Code as a force multiplier.

User-invocable

When the user types /retro, run this skill.

Arguments

• /retro — default: last 7 days
• /retro 24h — last 24 hours
• /retro 14d — last 14 days
• /retro 30d — last 30 days
• /retro compare — compare current window vs prior same-length window
• /retro compare 14d — compare with explicit window

Instructions

Parse the argument to determine the time window. Default to 7 days if no argument given. Use --since="N days ago", --since="N hours ago", or --since="N weeks ago" (for w units) for git log queries. All times should be reported in Pacific time (use TZ=America/Los_Angeles when converting timestamps).

Argument validation: If the argument doesn't match a number followed by d, h, or w, the word compare, or compare followed by a number and d/h/w, show this usage and stop:

Usage: /retro [window]
  /retro              — last 7 days (default)
  /retro 24h          — last 24 hours
  /retro 14d          — last 14 days
  /retro 30d          — last 30 days
  /retro compare      — compare this period vs prior period
  /retro compare 14d  — compare with explicit window

Step 1: Gather Raw Data

First, fetch origin and identify the current user:

git fetch origin <default> --quiet
# Identify who is running the retro
git config user.name
git config user.email

The name returned by git config user.name is "you" — the person reading this retro. All other authors are teammates. Use this to orient the narrative: "your" commits vs teammate contributions.

Run ALL of these git commands in parallel (they are independent):

# 1. All commits in window with timestamps, subject, hash, AUTHOR, files changed, insertions, deletions
git log origin/<default> --since="<window>" --format="%H|%aN|%ae|%ai|%s" --shortstat

# 2. Per-commit test vs total LOC breakdown with author
#    Each commit block starts with COMMIT:<hash>|<author>, followed by numstat lines.
#    Separate test files (matching test/|spec/|__tests__/) from production files.
git log origin/<default> --since="<window>" --format="COMMIT:%H|%aN" --numstat

# 3. Commit timestamps for session detection and hourly distribution (with author)
#    Use TZ=America/Los_Angeles for Pacific time conversion
TZ=America/Los_Angeles git log origin/<default> --since="<window>" --format="%at|%aN|%ai|%s" | sort -n

# 4. Files most frequently changed (hotspot analysis)
git log origin/<default> --since="<window>" --format="" --name-only | grep -v '^$' | sort | uniq -c | sort -rn

# 5. PR numbers from commit messages (extract #NNN patterns)
git log origin/<default> --since="<window>" --format="%s" | grep -oE '#[0-9]+' | sed 's/^#//' | sort -n | uniq | sed 's/^/#/'

# 6. Per-author file hotspots (who touches what)
git log origin/<default> --since="<window>" --format="AUTHOR:%aN" --name-only

# 7. Per-author commit counts (quick summary)
git shortlog origin/<default> --since="<window>" -sn --no-merges

# 8. Greptile triage history (if available)
cat ~/.gstack/greptile-history.md 2>/dev/null || true

# 9. TODOS.md backlog (if available)
cat TODOS.md 2>/dev/null || true

# 10. Test file count
find . -name '*.test.*' -o -name '*.spec.*' -o -name '*_test.*' -o -name '*_spec.*' 2>/dev/null | grep -v node_modules | wc -l

# 11. Regression test commits in window
git log origin/<default> --since="<window>" --oneline --grep="test(qa):" --grep="test(design):" --grep="test: coverage"

# 12. Test files changed in window
git log origin/<default> --since="<window>" --format="" --name-only | grep -E '\.(test|spec)\.' | sort -u | wc -l

Step 2: Compute Metrics

Calculate and present these metrics in a summary table:

Metric	Value
Commits to main	N
Contributors	N
PRs merged	N
Total insertions	N
Total deletions	N
Net LOC added	N
Test LOC (insertions)	N
Test LOC ratio	N%
Version range	vX.Y.Z.W → vX.Y.Z.W
Active days	N
Detected sessions	N
Avg LOC/session-hour	N
Greptile signal	N% (Y catches, Z FPs)
Test Health	N total tests · M added this period · K regression tests

Then show a per-author leaderboard immediately below:

Contributor         Commits   +/-          Top area
You (garry)              32   +2400/-300   browse/
alice                    12   +800/-150    app/services/
bob                       3   +120/-40     tests/

Sort by commits descending. The current user (from git config user.name) always appears first, labeled "You (name)".

Greptile signal (if history exists): Read ~/.gstack/greptile-history.md (fetched in Step 1, command 8). Filter entries within the retro time window by date. Count entries by type: fix, fp, already-fixed. Compute signal ratio: (fix + already-fixed) / (fix + already-fixed + fp). If no entries exist in the window or the file doesn't exist, skip the Greptile metric row. Skip unparseable lines silently.

Backlog Health (if TODOS.md exists): Read TODOS.md (fetched in Step 1, command 9). Compute:

• Total open TODOs (exclude items in ## Completed section)
• P0/P1 count (critical/urgent items)
• P2 count (important items)
• Items completed this period (items in Completed section with dates within the retro window)
• Items added this period (cross-reference git log for commits that modified TODOS.md within the window)

Include in the metrics table:

| Backlog Health | N open (X P0/P1, Y P2) · Z completed this period |

If TODOS.md doesn't exist, skip the Backlog Health row.

Step 3: Commit Time Distribution

Show hourly histogram in Pacific time using bar chart:

Hour  Commits  ████████████████
 00:    4      ████
 07:    5      █████
 ...

Identify and call out:

• Peak hours
• Dead zones
• Whether pattern is bimodal (morning/evening) or continuous
• Late-night coding clusters (after 10pm)

Step 4: Work Session Detection

Detect sessions using 45-minute gap threshold between consecutive commits. For each session report:

• Start/end time (Pacific)
• Number of commits
• Duration in minutes

Classify sessions:

• Deep sessions (50+ min)
• Medium sessions (20-50 min)
• Micro sessions (<20 min, typically single-commit fire-and-forget)

Calculate:

• Total active coding time (sum of session durations)
• Average session length
• LOC per hour of active time

Step 5: Commit Type Breakdown

Categorize by conventional commit prefix (feat/fix/refactor/test/chore/docs). Show as percentage bar:

feat:     20  (40%)  ████████████████████
fix:      27  (54%)  ███████████████████████████
refactor:  2  ( 4%)  ██

Flag if fix ratio exceeds 50% — this signals a "ship fast, fix fast" pattern that may indicate review gaps.

Step 6: Hotspot Analysis

Show top 10 most-changed files. Flag:

• Files changed 5+ times (churn hotspots)
• Test files vs production files in the hotspot list
• VERSION/CHANGELOG frequency (version discipline indicator)

Step 7: PR Size Distribution

From commit diffs, estimate PR sizes and bucket them:

• Small (<100 LOC)
• Medium (100-500 LOC)
• Large (500-1500 LOC)
• XL (1500+ LOC) — flag these with file counts

Step 8: Focus Score + Ship of the Week

Focus score: Calculate the percentage of commits touching the single most-changed top-level directory (e.g., app/services/, app/views/). Higher score = deeper focused work. Lower score = scattered context-switching. Report as: "Focus score: 62% (app/services/)"

Ship of the week: Auto-identify the single highest-LOC PR in the window. Highlight it:

• PR number and title
• LOC changed
• Why it matters (infer from commit messages and files touched)

Step 9: Team Member Analysis

For each contributor (including the current user), compute:

1. Commits and LOC — total commits, insertions, deletions, net LOC
2. Areas of focus — which directories/files they touched most (top 3)
3. Commit type mix — their personal feat/fix/refactor/test breakdown
4. Session patterns — when they code (their peak hours), session count
5. Test discipline — their personal test LOC ratio
6. Biggest ship — their single highest-impact commit or PR in the window

For the current user ("You"): This section gets the deepest treatment. Include all the detail from the solo retro — session analysis, time patterns, focus score. Frame it in first person: "Your peak hours...", "Your biggest ship..."

For each teammate: Write 2-3 sentences covering what they worked on and their pattern. Then:

• Praise (1-2 specific things): Anchor in actual commits. Not "great work" — say exactly what was good. Examples: "Shipped the entire auth middleware rewrite in 3 focused sessions with 45% test coverage", "Every PR under 200 LOC — disciplined decomposition."
• Opportunity for growth (1 specific thing): Frame as a leveling-up suggestion, not criticism. Anchor in actual data. Examples: "Test ratio was 12% this week — adding test coverage to the payment module before it gets more complex would pay off", "5 fix commits on the same file suggest the original PR could have used a review pass."

If only one contributor (solo repo): Skip the team breakdown and proceed as before — the retro is personal.

If there are Co-Authored-By trailers: Parse Co-Authored-By: lines in commit messages. Credit those authors for the commit alongside the primary author. Note AI co-authors (e.g., [e-mail]) but do not include them as team members — instead, track "AI-assisted commits" as a separate metric.

Step 10: Week-over-Week Trends (if window >= 14d)

If the time window is 14 days or more, split into weekly buckets and show trends:

• Commits per week (total and per-author)
• LOC per week
• Test ratio per week
• Fix ratio per week
• Session count per week

Step 11: Streak Tracking

Count consecutive days with at least 1 commit to origin/, going back from today. Track both team streak and personal streak:

# Team streak: all unique commit dates (Pacific time) — no hard cutoff
TZ=America/Los_Angeles git log origin/<default> --format="%ad" --date=format:"%Y-%m-%d" | sort -u

# Personal streak: only the current user's commits
TZ=America/Los_Angeles git log origin/<default> --author="<user_name>" --format="%ad" --date=format:"%Y-%m-%d" | sort -u

Count backward from today — how many consecutive days have at least one commit? This queries the full history so streaks of any length are reported accurately. Display both:

• "Team shipping streak: 47 consecutive days"
• "Your shipping streak: 32 consecutive days"

Step 12: Load History & Compare

Before saving the new snapshot, check for prior retro history:

ls -t .context/retros/*.json 2>/dev/null

If prior retros exist: Load the most recent one using the Read tool. Calculate deltas for key metrics and include a Trends vs Last Retro section:

                    Last        Now         Delta
Test ratio:         22%    →    41%         ↑19pp
Sessions:           10     →    14          ↑4
LOC/hour:           200    →    350         ↑75%
Fix ratio:          54%    →    30%         ↓24pp (improving)
Commits:            32     →    47          ↑47%
Deep sessions:      3      →    5           ↑2

If no prior retros exist: Skip the comparison section and append: "First retro recorded — run again next week to see trends."

Reference Files

For detailed patterns and code examples, see references/output-format.md.