---

name: retro preamble-tier: 2 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. Use when asked to "weekly retro", "what did we ship", or "engineering retrospective". Proactively suggest at the end of a work week or sprint. (gstack) allowed-tools:

• Bash
• Read
• Write
• Glob
• AskUserQuestion triggers:
• weekly retro
• what did we ship
• engineering retrospective gbrain: schema: 1 context_queries:
  • id: prior-retros kind: filesystem

    #2552: /retro writes .context/retros/*.json (repo-local; see the save

    step below) — the old ~/.gstack/.../retros/*.md glob matched a

    directory and extension nothing ever writes, so this query was dead.

    glob: ".context/retros/*.json" sort: mtime_desc limit: 5 render_as: "## Prior retros for this project"
  • id: recent-timeline kind: filesystem glob: "~/.gstack/projects/{repo_slug}/timeline.jsonl" tail: 30 render_as: "## Recent timeline events"
  • id: recent-learnings kind: filesystem glob: "~/.gstack/projects/{repo_slug}/learnings.jsonl" tail: 10 render_as: "## Recent learnings"

---

{{PREAMBLE}}

{{BASE_BRANCH_DETECT}}

/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
• /retro global — cross-project retro across all AI coding tools (7d default)
• /retro global 14d — cross-project retro with explicit window

{{GBRAIN_CONTEXT_LOAD}}

{{SECTION_INDEX:retro}}

Instructions

Parse the argument to determine the time window. Default to 7 days if no argument given. All times should be reported in the user's local timezone (use the system default — do NOT set TZ).

Midnight-aligned windows: For day (d) and week (w) units, compute an absolute start date at local midnight, not a relative string. For example, if today is 2026-03-18 and the window is 7 days: the start date is 2026-03-11. Use --since "2026-03-11T00:00:00" — the explicit T00:00:00 suffix ensures git starts from midnight. Without it, git uses the current wall-clock time (e.g., --since "2026-03-11" at 11pm means 11pm, not midnight). For week units, multiply by 7 to get days (e.g., 2w = 14 days back). For hour (h) units, use --since "N hours ago" since midnight alignment does not apply to sub-day windows. Compute "today" from the user-visible ## currentDate tag in the session reminder — NEVER from date (the system clock can be hours off in containerized harnesses). If you cannot reliably compute "today", stop and ask the user via AskUserQuestion rather than proceeding.

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

Usage: /retro [window | compare | global]
  /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
  /retro global       — cross-project retro across all AI tools (7d default)
  /retro global 14d   — cross-project retro with explicit window

If the first argument is global: Skip the normal repo-scoped retro (Steps 1-14). Instead, follow the Global Retrospective flow at the end of this document. The optional second argument is the time window (default 7d). This mode does NOT require being inside a git repo.

{{LEARNINGS_SEARCH}}

Step 0.5: Freshness pre-flight (fetch)

Refresh origin/<default> so the retro doesn't misreport against a stale local ref. If the repo has no origin remote this fails harmlessly — the metrics script (Step 1) falls back to the local branch and its guard lines disclose it:

git fetch origin <default> --quiet 2>/dev/null \
  || echo "RETRO_FETCH: failed (offline or no remote) — proceeding against last-known refs"

Remember whether the fetch succeeded — the stale-base guard in Step 1 only BLOCKs when it did.

Step 1: Gather Metrics (one command)

All raw data gathering and metric computation runs through gstack-retro-metrics — one command instead of a dozen git pipelines. Substitute the base branch detected in Step 0 and the midnight-aligned start computed above:

_RM="$HOME/.claude/skills/gstack/bin/gstack-retro-metrics"
[ -x "$_RM" ] || _RM=".claude/skills/gstack/bin/gstack-retro-metrics"
"$_RM" --base "<default>" --since "<since>" \
  || echo "RETRO_METRICS: unavailable — stale install (compute metrics manually from the steps below)"

Read the labeled METRIC_NAME: value lines — they feed every step below. Degraded mode: if RETRO_METRICS_PROTO: 1 is missing from the output, the install is stale; compute each metric manually with git commands, using the metric definitions in Steps 2-11 as the spec.

Identity: USER_NAME is "you" — the person reading this retro. All other authors are teammates. Orient the narrative around this: "your" commits vs teammate contributions.

Stale-base + bad-today-anchor guard. The script echoes GUARD_LATEST_COMMIT: <DATE> (newest commit on the analyzed ref). If "today" drifts (model session-context error) or the local origin/<default> is materially behind the remote, the window returns zero or near-zero commits and the retro would fabricate a coherent-looking narrative from nothing. Evaluate in this order:

1. If GUARD_REMOTE: none or GUARD_HEAD: detached or the Step 0.5 fetch failed: proceed, but carry the disclosure into the narrative ("offline run, window not freshness-verified") rather than silently misreporting.
2. If the Step 0.5 fetch succeeded AND the GUARD_LATEST_COMMIT date is older than (today − window-days): BLOCK with: "Retro window is stale. Latest commit on origin/<default> was <DATE>, but the window covers <since> to <today>. This usually means either (a) today's date is wrong in this session or (b) origin/<default> is materially behind the remote. Confirm today's date via the session reminder; if today is correct, run git fetch origin <default> manually and re-run /retro." Stop the skill until the user resolves.
3. Otherwise, write: "RETRO_GUARD: latest commit <DATE> within window — proceeding."

Also check RETRO_REF: if it is not origin/<default> (local-only repo, missing remote branch), disclose which ref the retro analyzed.

Metric line reference (what the script emits):

| Line | Meaning | |------|---------| | COMMIT: hash\|author\|datetime\|+ins/-del\|subject | One per commit, newest first (capped at 300) — the raw material for narrative anchoring | | COMMITS / MERGE_COMMITS / CONTRIBUTORS | Window totals on the analyzed ref | | INSERTIONS / DELETIONS / NET_LOC | Raw LOC | | LOGICAL_SLOC_ADDED | Non-blank, non-comment added lines — the primary code-volume metric | | TEST_INSERTIONS / TEST_RATIO | Test LOC (test/spec paths + .test./.spec. suffixes) and its share of insertions | | WEIGHTED_COMMITS | Commits × files-touched, capped at 20 per commit | | ACTIVE_DAYS | Distinct local dates with commits | | SESSIONS / DEEP_SESSIONS / MEDIUM_SESSIONS / MICRO_SESSIONS | 45-minute-gap session detection: deep 50+ min, medium 20-50, micro <20 | | TOTAL_ACTIVE_MINUTES / AVG_SESSION_MINUTES / LOC_PER_SESSION_HOUR | Session time aggregates (LOC/hour pre-rounded to nearest 50) | | COMMIT_TYPES / FIX_RATIO | Conventional-commit prefix mix | | COMMIT_SIZE_BUCKETS | small <100 / medium 100-500 / large 500-1500 / xl 1500+ LOC per commit | | HOURS / PEAK_HOUR | Hourly commit histogram (local time), nonzero hours only | | FOCUS_SCORE | % of file changes in the single busiest top-level directory | | BIGGEST_COMMIT | Highest-LOC commit in the window (ship-of-the-week candidate) | | HOTSPOT: count file | Top 10 most-changed files | | AUTHOR: name\|commits\|ins\|del\|test_ratio\|top_areas\|types\|peak_hour | Per-contributor rollup, sorted by commits desc | | AUTHOR_BIGGEST: name\|hash\|loc\|subject | Each contributor's biggest ship | | COAUTHOR: hash\|name / AI_ASSISTED_COMMITS | Human co-author credit lines; count of commits with AI trailers | | WEEK: wN\|commits\|ins\|del\|test_ratio | Weekly buckets, w0 = newest (for Step 10 trends) | | PR_REFS / PRS_REFERENCED | PR/MR numbers from commit subjects (GitHub #NNN, GitLab !NNN) | | TEST_FILES_TOTAL / TEST_FILES_CHANGED / REGRESSION_TEST_COMMITS / REGRESSION_COMMIT | Test health: repo-wide test file count, test files changed in window, test(qa): / test(design): / test: coverage commits | | VERSION_RANGE | First → last VERSION file value in the window (when tracked) | | TEAM_STREAK / USER_STREAK | Consecutive commit days with anchor date (Step 11) | | RETRO_CONTEXT / GREPTILE_HISTORY / TODOS_FILE / SKILL_USAGE_LOG / EUREKA_LOG | Presence of optional inputs — Read the ones marked present |

Optional inputs (Read each file the script marks present):

• RETRO_CONTEXT: present → Read ~/.gstack/retro-context.md. It is user-authored and may contain meeting notes, calendar events, decisions, and other context that doesn't appear in git history. Incorporate it into the retro narrative where relevant.
• GREPTILE_HISTORY: present → Read ~/.gstack/greptile-history.md. Filter entries to the retro window by date. Count by type: fix, fp, already-fixed. Signal ratio = (fix + already-fixed) / (fix + already-fixed + fp). Skip unparseable lines silently; if no entries fall in the window, skip the Greptile metric row.
• TODOS_FILE: present → Read TODOS.md. Compute: total open TODOs (exclude the ## Completed section), P0/P1 count, P2 count, items completed this period (Completed entries dated within the window), items added this period (cross-reference COMMIT: lines that touched TODOS.md).
• SKILL_USAGE_LOG: present → Read ~/.gstack/analytics/skill-usage.jsonl. Filter to the window by ts. Separate skill activations (no event field) from hook fires (event: "hook_fire"). Aggregate by skill name.
• EUREKA_LOG: present → Read ~/.gstack/analytics/eureka.jsonl. Filter to the window by ts. For each eureka moment note the skill that flagged it, the branch, and a one-line summary of the insight.

Step 2: Compute Metrics

Present these metrics in a summary table, straight from the metric lines:

| Metric | Value | |--------|-------| | Features shipped (from CHANGELOG + merged PR titles) | N | | Commits to main | N | | Weighted commits (WEIGHTED_COMMITS) | N | | Contributors | N | | PRs merged | N | | Logical SLOC added (LOGICAL_SLOC_ADDED — primary code-volume metric) | N | | Raw LOC: insertions | N | | Raw LOC: deletions | N | | Raw LOC: net | 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 raw LOC/session-hour | N | | Greptile signal | N% (Y catches, Z FPs) | | Test Health | N total tests · M added this period · K regression tests |

Metric order rationale (V1): features shipped leads — what users got. Commits and weighted commits reflect intent-to-ship. Logical SLOC added reflects real new functionality. Raw LOC is demoted to context because AI inflates it; ten lines of a good fix is not less shipping than ten thousand lines of scaffold. See docs/designs/PLAN_TUNING_V1.md §Workstream C.

Then show a per-author leaderboard immediately below, from the AUTHOR: lines:

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 (USER_NAME) always appears first, labeled "You (name)".

Conditional rows (skip each when its input is absent or empty in the window):

| Backlog Health | N open (X P0/P1, Y P2) · Z completed this period |
| Skill Usage | /ship(12) /qa(8) /review(5) · 3 safety hook fires |
| Eureka Moments | 2 this period |

If eureka moments exist, list them:

  EUREKA /office-hours (branch: garrytan/auth-rethink): "Session tokens don't need server storage — browser crypto API makes client-side JWT validation viable"
  EUREKA /plan-eng-review (branch: garrytan/cache-layer): "Redis isn't needed here — Bun's built-in LRU cache handles this workload"

Step 3: Commit Time Distribution

Render the HOURS line as an hourly histogram in local time:

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

Sessions are pre-computed with a 45-minute gap threshold between consecutive commits (SESSIONS, DEEP_SESSIONS 50+ min, MEDIUM_SESSIONS 20-50 min, MICRO_SESSIONS <20 min — typically single-commit fire-and-forget). Report:

• Session count and the deep/medium/micro split
• Total active coding time (TOTAL_ACTIVE_MINUTES) and average session length
• LOC per hour of active time (LOC_PER_SESSION_HOUR)

Step 5: Commit Type Breakdown

Render COMMIT_TYPES (feat/fix/refactor/test/chore/docs) as a 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 the HOTSPOT lines (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

Report COMMIT_SIZE_BUCKETS:

• Small (<100 LOC)
• Medium (100-500 LOC)
• Large (500-1500 LOC)
• XL (1500+ LOC)

Step 8: Focus Score + Ship of the Week

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

Ship of the week: BIGGEST_COMMIT is the highest-LOC change in the window. Highlight it:

• PR number (match against PR_REFS / the subject) 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), the AUTHOR: line carries commits, insertions, deletions, test ratio, top areas, commit type mix, and peak hour; AUTHOR_BIGGEST: carries their single highest-impact commit. Use the COMMIT: lines to anchor everything in actual work.

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.

Co-author credit: COAUTHOR: lines carry human Co-Authored-By: trailers — credit those authors for the commit alongside the primary author. AI co-authors (e.g., noreply@anthropic.com) are counted in AI_ASSISTED_COMMITS instead — track "AI-assisted commits" as a separate metric, never as a team member.

{{LEARNINGS_LOG}}

{{GBRAIN_SAVE_RESULTS}}

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

If the time window is 14 days or more, use the WEEK: lines (w0 = the week containing the newest commit) to show trends:

• Commits per week (total; per-author from the COMMIT: lines)
• LOC per week
• Test ratio per week
• Fix ratio per week

Step 11: Streak Tracking

TEAM_STREAK and USER_STREAK count consecutive days with at least 1 commit (full history, no cutoff), anchored at the newest commit date — not at today, because the script never trusts the system clock. Interpret against today from the session reminder:

• If the anchor date is today or yesterday, the streak is live: "Team shipping streak: 47 consecutive days" / "Your shipping streak: 32 consecutive days"
• If the anchor is older, the streak is broken: report 0 days and note the last shipping day.

Step 12: Load History & Compare

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

setopt +o nomatch 2>/dev/null || true  # zsh compat
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."

Step 13: Save Retro History

After computing all metrics (including streak) and loading any prior history for comparison, save a JSON snapshot:

mkdir -p .context/retros

Determine the next sequence number for today (substitute the actual date for $(date +%Y-%m-%d)):

setopt +o nomatch 2>/dev/null || true  # zsh compat
# Count existing retros for today to get next sequence number
today=$(date +%Y-%m-%d)
existing=$(ls .context/retros/${today}-*.json 2>/dev/null | wc -l | tr -d ' ')
next=$((existing + 1))
# Save as .context/retros/${today}-${next}.json

Use the Write tool to save the JSON file with this schema:

{
  "date": "2026-03-08",
  "window": "7d",
  "metrics": {
    "commits": 47,
    "contributors": 3,
    "prs_merged": 12,
    "insertions": 3200,
    "deletions": 800,
    "net_loc": 2400,
    "test_loc": 1300,
    "test_ratio": 0.41,
    "active_days": 6,
    "sessions": 14,
    "deep_sessions": 5,
    "avg_session_minutes": 42,
    "loc_per_session_hour": 350,
    "feat_pct": 0.40,
    "fix_pct": 0.30,
    "peak_hour": 22,
    "ai_assisted_commits": 32
  },
  "authors": {
    "Garry Tan": { "commits": 32, "insertions": 2400, "deletions": 300, "test_ratio": 0.41, "top_area": "browse/" },
    "Alice": { "commits": 12, "insertions": 800, "deletions": 150, "test_ratio": 0.35, "top_area": "app/services/" }
  },
  "version_range": ["1.16.0.0", "1.16.1.0"],
  "streak_days": 47,
  "tweetable": "Week of Mar 1: 47 commits (3 contributors), 3.2k LOC, 38% tests, 12 PRs, peak: 10pm",
  "greptile": {
    "fixes": 3,
    "fps": 1,
    "already_fixed": 2,
    "signal_pct": 83
  }
}

Note: Only include the greptile field if ~/.gstack/greptile-history.md exists and has entries within the time window. Only include the backlog field if TODOS.md exists. Only include the test_health field if test files were found (TEST_FILES_TOTAL > 0). If any has no data, omit the field entirely.

Include test health data in the JSON when test files exist:

  "test_health": {
    "total_test_files": 47,
    "tests_added_this_period": 5,
    "regression_test_commits": 3,
    "test_files_changed": 8
  }

Include backlog data in the JSON when TODOS.md exists:

  "backlog": {
    "total_open": 28,
    "p0_p1": 2,
    "p2": 8,
    "completed_this_period": 3,
    "added_this_period": 1
  }

Step 14: Write the Narrative

{{SECTION:report-format}}

---

Global Retrospective Mode

When the user runs /retro global (or /retro global 14d), follow this flow instead of the repo-scoped Steps 1-14. This mode works from any directory — it does NOT require being inside a git repo.

Global Step 1: Compute time window

Same midnight-aligned logic as the regular retro. Default 7d. The second argument after global is the window (e.g., 14d, 30d, 24h).

Global Step 2: Run discovery

Locate and run the discovery script using this fallback chain:

DISCOVER_BIN=""
[ -x ~/.claude/skills/gstack/bin/gstack-global-discover ] && DISCOVER_BIN=~/.claude/skills/gstack/bin/gstack-global-discover
[ -z "$DISCOVER_BIN" ] && [ -x .claude/skills/gstack/bin/gstack-global-discover ] && DISCOVER_BIN=.claude/skills/gstack/bin/gstack-global-discover
[ -z "$DISCOVER_BIN" ] && which gstack-global-discover >/dev/null 2>&1 && DISCOVER_BIN=$(which gstack-global-discover)
[ -z "$DISCOVER_BIN" ] && [ -f bin/gstack-global-discover.ts ] && DISCOVER_BIN="bun run bin/gstack-global-discover.ts"
echo "DISCOVER_BIN: $DISCOVER_BIN"

If no binary is found, tell the user: "Discovery script not found. Run bun run build in the gstack directory to compile it." and stop.

Run the discovery:

$DISCOVER_BIN --since "<window>" --format json 2>/tmp/gstack-discover-stderr

Read the stderr output from /tmp/gstack-discover-stderr for diagnostic info. Parse the JSON output from stdout.

If total_sessions is 0, say: "No AI coding sessions found in the last <window>. Try a longer window: /retro global 30d" and stop.

Global Step 3: Run git log on each discovered repo

For each repo in the discovery JSON's repos array, find the first valid path in paths[] (directory exists with .git/). If no valid path exists, skip the repo and note it.

For local-only repos (where remote starts with local:): skip git fetch and use the local default branch. Use git log HEAD instead of git log origin/$DEFAULT.

For repos with remotes:

git -C <path> fetch origin --quiet 2>/dev/null

Detect the default branch for each repo: first try git symbolic-ref refs/remotes/origin/HEAD, then check common branch names (main, master), then fall back to git rev-parse --abbrev-ref HEAD. Use the detected branch as <default> in the commands below.

# Commits with stats
git -C <path> log origin/$DEFAULT --since="<start_date>T00:00:00" --format="%H|%aN|%ai|%s" --shortstat

# Commit timestamps for session detection, streak, and context switching
git -C <path> log origin/$DEFAULT --since="<start_date>T00:00:00" --format="%at|%aN|%ai|%s" | sort -n

# Per-author commit counts
git -C <path> shortlog origin/$DEFAULT --since="<start_date>T00:00:00" -sn --no-merges

# PR/MR numbers from commit messages (GitHub #NNN, GitLab !NNN)
git -C <path> log origin/$DEFAULT --since="<start_date>T00:00:00" --format="%s" | grep -oE '[#!][0-9]+' | sort -t'#' -k1 | uniq

For repos that fail (deleted paths, network errors): skip and note "N repos could not be reached."

Global Step 4: Compute global shipping streak

For each repo, get commit dates (capped at 365 days):

git -C <path> log origin/$DEFAULT --since="365 days ago" --format="%ad" --date=format:"%Y-%m-%d" | sort -u

Union all dates across all repos. Count backward from today — how many consecutive days have at least one commit to ANY repo? If the streak hits 365 days, display as "365+ days".

Global Step 5: Compute context switching metric

From the commit timestamps gathered in Step 3, group by date. For each date, count how many distinct repos had commits that day. Report:

• Average repos/day
• Maximum repos/day
• Which days were focused (1 repo) vs. fragmented (3+ repos)

Global Step 6: Per-tool productivity patterns

From the discovery JSON, analyze tool usage patterns:

• Which AI tool is used for which repos (exclusive vs. shared)
• Session count per tool
• Behavioral patterns (e.g., "Codex used exclusively for myapp, Claude Code for everything else")

Global Step 7: Aggregate and generate narrative

Structure the output with the shareable personal card first, then the full team/project breakdown below. The personal card is designed to be screenshot-friendly — everything someone would want to share on X/Twitter in one clean block.

---

Tweetable summary (first line, before everything else):

Week of Mar 14: 5 projects, 138 commits, 250k LOC across 5 repos | 48 AI sessions | Streak: 52d 🔥

🚀 Your Week: [user name] — [date range]

This section is the shareable personal card. It contains ONLY the current user's stats — no team data, no project breakdowns. Designed to screenshot and post.

Use the user identity from git config user.name to filter all per-repo git data. Aggregate across all repos to compute personal totals.

Render as a single visually clean block. Left border only — no right border (LLMs can't align right borders reliably). Pad repo names to the longest name so columns align cleanly. Never truncate project names.

╔═══════════════════════════════════════════════════════════════
║  [USER NAME] — Week of [date]
╠═══════════════════════════════════════════════════════════════
║
║  [N] commits across [M] projects
║  +[X]k LOC added · [Y]k LOC deleted · [Z]k net
║  [N] AI coding sessions (CC: X, Codex: Y, Gemini: Z)
║  [N]-day shipping streak 🔥
║
║  PROJECTS
║  ─────────────────────────────────────────────────────────
║  [repo_name_full]        [N] commits    +[X]k LOC    [solo/team]
║  [repo_name_full]        [N] commits    +[X]k LOC    [solo/team]
║  [repo_name_full]        [N] commits    +[X]k LOC    [solo/team]
║
║  SHIP OF THE WEEK
║  [PR title] — [LOC] lines across [N] files
║
║  TOP WORK
║  • [1-line description of biggest theme]
║  • [1-line description of second theme]
║  • [1-line description of third theme]
║
║  Powered by gstack
╚═══════════════════════════════════════════════════════════════

Rules for the personal card:

• Only show repos where the user has commits. Skip repos with 0 commits.
• Sort repos by user's commit count descending.
• Never truncate repo names. Use the full repo name (e.g., analyze_transcripts not analyze_trans). Pad the name column to the longest repo name so all columns align. If names are long, widen the box — the box width adapts to content.
• For LOC, use "k" formatting for thousands (e.g., "+64.0k" not "+64010").
• Role: "solo" if user is the only contributor, "team" if others contributed.
• Ship of the Week: the user's single highest-LOC PR across ALL repos.
• Top Work: 3 bullet points summarizing the user's major themes, inferred from commit messages. Not individual commits — synthesize into themes. E.g., "Built /retro global — cross-project retrospective with AI session discovery" not "feat: gstack-global-discover" + "feat: /retro global template".
• The card must be self-contained. Someone seeing ONLY this block should understand the user's week without any surrounding context.
• Do NOT include team members, project totals, or context switching data here.

Personal streak: Use the user's own commits across all repos (filtered by --author) to compute a personal streak, separate from the team streak.

---

Global Engineering Retro: [date range]

Everything below is the full analysis — team data, project breakdowns, patterns. This is the "deep dive" that follows the shareable card.

All Projects Overview

| Metric | Value | |--------|-------| | Projects active | N | | Total commits (all repos, all contributors) | N | | Total LOC | +N / -N | | AI coding sessions | N (CC: X, Codex: Y, Gemini: Z) | | Active days | N | | Global shipping streak (any contributor, any repo) | N consecutive days | | Context switches/day | N avg (max: M) |

Per-Project Breakdown

For each repo (sorted by commits descending):

• Repo name (with % of total commits)
• Commits, LOC, PRs merged, top contributor
• Key work (inferred from commit messages)
• AI sessions by tool

Your Contributions (sub-section within each project): For each project, add a "Your contributions" block showing the current user's personal stats within that repo. Use the user identity from git config user.name to filter. Include:

• Your commits / total commits (with %)
• Your LOC (+insertions / -deletions)
• Your key work (inferred from YOUR commit messages only)
• Your commit type mix (feat/fix/refactor/chore/docs breakdown)
• Your biggest ship in this repo (highest-LOC commit or PR)

If the user is the only contributor, say "Solo project — all commits are yours." If the user has 0 commits in a repo (team project they didn't touch this period), say "No commits this period — [N] AI sessions only." and skip the breakdown.

Format:

**Your contributions:** 47/244 commits (19%), +4.2k/-0.3k LOC
  Key work: Writer Chat, email blocking, security hardening
  Biggest ship: PR #605 — Writer Chat eats the admin bar (2,457 ins, 46 files)
  Mix: feat(3) fix(2) chore(1)

Cross-Project Patterns

• Time allocation across projects (% breakdown, use YOUR commits not total)
• Peak productivity hours aggregated across all repos
• Focused vs. fragmented days
• Context switching trends

Tool Usage Analysis

Per-tool breakdown with behavioral patterns:

• Claude Code: N sessions across M repos — patterns observed
• Codex: N sessions across M repos — patterns observed
• Gemini: N sessions across M repos — patterns observed

Ship of the Week (Global)

Highest-impact PR across ALL projects. Identify by LOC and commit messages.

3 Cross-Project Insights

What the global view reveals that no single-repo retro could show.

3 Habits for Next Week

Considering the full cross-project picture.

---

Global Step 8: Load history & compare

setopt +o nomatch 2>/dev/null || true  # zsh compat
ls -t ~/.gstack/retros/global-*.json 2>/dev/null | head -5

Only compare against a prior retro with the same window value (e.g., 7d vs 7d). If the most recent prior retro has a different window, skip comparison and note: "Prior global retro used a different window — skipping comparison."

If a matching prior retro exists, load it with the Read tool. Show a Trends vs Last Global Retro table with deltas for key metrics: total commits, LOC, sessions, streak, context switches/day.

If no prior global retros exist, append: "First global retro recorded — run again next week to see trends."

Global Step 9: Save snapshot

mkdir -p ~/.gstack/retros

Determine the next sequence number for today:

setopt +o nomatch 2>/dev/null || true  # zsh compat
today=$(date +%Y-%m-%d)
existing=$(ls ~/.gstack/retros/global-${today}-*.json 2>/dev/null | wc -l | tr -d ' ')
next=$((existing + 1))

Use the Write tool to save JSON to ~/.gstack/retros/global-${today}-${next}.json:

{
  "type": "global",
  "date": "2026-03-21",
  "window": "7d",
  "projects": [
    {
      "name": "gstack",
      "remote": "<detected from git remote get-url origin, normalized to HTTPS>",
      "commits": 47,
      "insertions": 3200,
      "deletions": 800,
      "sessions": { "claude_code": 15, "codex": 3, "gemini": 0 }
    }
  ],
  "totals": {
    "commits": 182,
    "insertions": 15300,
    "deletions": 4200,
    "projects": 5,
    "active_days": 6,
    "sessions": { "claude_code": 48, "codex": 8, "gemini": 3 },
    "global_streak_days": 52,
    "avg_context_switches_per_day": 2.1
  },
  "tweetable": "Week of Mar 14: 5 projects, 182 commits, 15.3k LOC | CC: 48, Codex: 8, Gemini: 3 | Focus: gstack (58%) | Streak: 52d"
}

---

Compare Mode

When the user runs /retro compare (or /retro compare 14d):

1. Run Steps 0.5-1 for the current window (default 7d) using the midnight-aligned start date (same logic as the main retro — e.g., if today is 2026-03-18 and window is 7d, --since "2026-03-11T00:00:00")
2. Run gstack-retro-metrics a second time for the immediately prior same-length window, using both --since and --until with midnight-aligned dates to avoid overlap (e.g., for a 7d window starting 2026-03-11: --since "2026-03-04T00:00:00" --until "2026-03-11T00:00:00")
3. Show a side-by-side comparison table with deltas and arrows
4. Write a brief narrative highlighting the biggest improvements and regressions
5. Save only the current-window snapshot to .context/retros/ (same as a normal retro run); do not persist the prior-window metrics.

Tone

• Encouraging but candid, no coddling
• Specific and concrete — always anchor in actual commits/code
• Skip generic praise ("great job!") — say exactly what was good and why
• Frame improvements as leveling up, not criticism
• Praise should feel like something you'd actually say in a 1:1 — specific, earned, genuine
• Growth suggestions should feel like investment advice — "this is worth your time because..." not "you failed at..."
• Never compare teammates against each other negatively. Each person's section stands on its own.
• Keep total output around 3000-4500 words (slightly longer to accommodate team sections)
• Use markdown tables and code blocks for data, prose for narrative
• Output directly to the conversation — do NOT write to filesystem (except the .context/retros/ JSON snapshot)

Important Rules

• ALL narrative output goes directly to the user in the conversation. The ONLY file written is the .context/retros/ JSON snapshot.
• The metrics script analyzes origin/<default> (not local main which may be stale); when RETRO_REF says otherwise, disclose it
• Display all timestamps in the user's local timezone (do not override TZ)
• If COMMITS: 0, say so and suggest a different window
• Round LOC/hour to nearest 50 (the script pre-rounds LOC_PER_SESSION_HOUR)
• Treat merge commits as PR boundaries
• Do not read CLAUDE.md or other docs — this skill is self-contained
• On first run (no prior retros), skip comparison sections gracefully
• Global mode: Does NOT require being inside a git repo. Saves snapshots to ~/.gstack/retros/ (not .context/retros/). Gracefully skip AI tools that aren't installed. Only compare against prior global retros with the same window value. If streak hits 365d cap, display as "365+ days".