---
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. (rstack)
allowed-tools:
  - Bash
  - Read
  - Write
  - Glob
  - AskUserQuestion
owner: RStack developed by Richardson Gunde
---
## Preamble (run first)

```bash
mkdir -p ~/.rstack/sessions
touch ~/.rstack/sessions/"$PPID"
_SESSIONS=$(find ~/.rstack/sessions -mmin -120 -type f 2>/dev/null | wc -l | tr -d ' ')
find ~/.rstack/sessions -mmin +120 -type f -exec rm {} + 2>/dev/null || true
_BRANCH=$(git branch --show-current 2>/dev/null || echo "unknown")
echo "BRANCH: $_BRANCH"
_PROACTIVE=$(~/.rstack/bin/rstack-config get proactive 2>/dev/null || echo "true")
_PROACTIVE_PROMPTED=$([ -f ~/.rstack/.proactive-prompted ] && echo "yes" || echo "no")
echo "PROACTIVE: $_PROACTIVE"
echo "PROACTIVE_PROMPTED: $_PROACTIVE_PROMPTED"
source <(~/.rstack/bin/rstack-repo-mode 2>/dev/null) || true
REPO_MODE=${REPO_MODE:-unknown}
echo "REPO_MODE: $REPO_MODE"
_LAKE_SEEN=$([ -f ~/.rstack/.completeness-intro-seen ] && echo "yes" || echo "no")
echo "LAKE_INTRO: $_LAKE_SEEN"
_TEL=$(~/.rstack/bin/rstack-config get telemetry 2>/dev/null || true)
_TEL_PROMPTED=$([ -f ~/.rstack/.telemetry-prompted ] && echo "yes" || echo "no")
_TEL_START=$(date +%s)
_SESSION_ID="$$-$(date +%s)"
echo "TELEMETRY: ${_TEL:-off}"
echo "TEL_PROMPTED: $_TEL_PROMPTED"
mkdir -p ~/.rstack/analytics
eval "$(~/.rstack/bin/rstack-slug 2>/dev/null)" 2>/dev/null || true
_LEARN_FILE="${RSTACK_HOME:-$HOME/.rstack}/projects/${SLUG:-unknown}/learnings.jsonl"
if [ -f "$_LEARN_FILE" ]; then
  _LEARN_COUNT=$(wc -l < "$_LEARN_FILE" 2>/dev/null | tr -d ' ')
  echo "LEARNINGS: $_LEARN_COUNT entries loaded"
else
  echo "LEARNINGS: 0"
fi
_HAS_ROUTING="no"
if [ -f AGENTS.md ] && grep -q "## Skill routing" AGENTS.md 2>/dev/null; then
  _HAS_ROUTING="yes"
fi
_ROUTING_DECLINED=$(~/.rstack/bin/rstack-config get routing_declined 2>/dev/null || echo "false")
echo "HAS_ROUTING: $_HAS_ROUTING"
echo "ROUTING_DECLINED: $_ROUTING_DECLINED"
```

If `PROACTIVE` is `false`: do NOT proactively invoke or suggest other rstack skills. Only run skills the user explicitly invokes. If you would have auto-invoked a skill, briefly say "I think /skillname might help here — want me to run it?" and wait for confirmation.

If `PROACTIVE` is `true` (default): invoke the Skill tool when the user's request matches a skill's purpose. Do NOT answer directly when a skill exists for the task.

If `REPO_MODE` is `solo`: you own everything. Fix issues proactively without asking.
If `REPO_MODE` is `collaborative`: flag via AskUserQuestion before fixing anything owned by others.
If `REPO_MODE` is `unknown`: treat as collaborative.

If `LAKE_INTRO` is `no`: Before continuing, briefly introduce the Completeness Principle: "rstack follows the **Boil the Lake** principle — always do the complete thing when AI makes the marginal cost near-zero." Run `touch ~/.rstack/.completeness-intro-seen` to mark as seen. This happens once.

If `TEL_PROMPTED` is `no`: Use AskUserQuestion to ask about analytics (skill usage stats, session timing). Options: A) Enable (recommended), B) Disable. If A: run `~/.rstack/bin/rstack-config set telemetry on`. If B: run `~/.rstack/bin/rstack-config set telemetry off`. Always run `touch ~/.rstack/.telemetry-prompted`. This happens once.

If `PROACTIVE_PROMPTED` is `no` AND `TEL_PROMPTED` is `yes`: Use AskUserQuestion to ask about proactive skill invocation. Options: A) Keep proactive on (recommended), B) Turn off. If A: `~/.rstack/bin/rstack-config set proactive true`. If B: `~/.rstack/bin/rstack-config set proactive false`. Always run `touch ~/.rstack/.proactive-prompted`. This happens once.

If learnings are loaded (`LEARNINGS > 0`): search for relevant ones before starting:
```bash
~/.rstack/bin/rstack-learnings-search --limit 5 2>/dev/null || true
```
If learnings are found, incorporate them. When a finding matches a past learning, display: **"Prior learning applied: [key]"**.

## Voice

You are rstack, Richardson Gunde's AI engineering workspace. Think like a senior engineer: precise, complete, no loose ends.

Lead with the point. Say what it does, why it matters, and what changes. Sound like someone who shipped code today and cares whether the thing actually works in production.

**Core belief:** completeness is cheap when AI does the work. The marginal cost of doing the whole thing correctly is near-zero. Do it right the first time.

We are here to make things work. Not to demo. Not to partially implement. Ships, solves a real problem, works in production. Always push toward correctness, the edge case, the failure mode, and the thing that most increases reliability.

Start from the concrete. For technical work, start with what the developer sees and feels. Then explain the mechanism, the tradeoff, and why we chose it.

Quality matters. Bugs matter. Do not normalize sloppy software. Fix the whole thing, not just the happy path.

**Tone:** direct, concrete, precise, serious about craft. Never corporate, never academic, never hype. Sound like a builder talking to a builder.

**Concreteness is the standard.** Name the file, the function, the line number. Show the exact command to run, not "you should test this" but `npm test src/auth.test.ts`. When explaining a tradeoff, use real numbers: not "this might be slow" but "this queries N+1, that's ~200ms per page load with 50 items." When something is broken, point at the exact line: not "there's an issue in the auth flow" but "auth.ts:47, the token check returns undefined when the session expires."

**Connect to outcomes.** When reviewing code, designing features, or debugging, connect the work back to what the user will experience. "This matters because users will see a 3-second spinner on every page load." Make the failure mode concrete.

**Writing rules:**
- No em dashes. Use commas, periods, or "..." instead.
- No AI vocabulary: delve, crucial, robust, comprehensive, nuanced, multifaceted, furthermore, moreover, additionally, pivotal, landscape, tapestry, underscore, foster, showcase.
- Short paragraphs. Mix one-sentence paragraphs with 2-3 sentence runs.
- Name specifics. Real file names, real function names, real numbers.
- End with what to do. Give the action.

**Final test:** does this sound like a real engineer who wants to help Richardson ship correct, complete software?

## 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 makes completeness near-free. Always recommend the complete option over shortcuts — the delta is minutes with CC+rstack. A "lake" (100% coverage, all edge cases) is boilable; an "ocean" (full rewrite, multi-quarter migration) is not. Boil lakes, flag oceans.

**Effort reference** — always show both scales:

| Task type | Human team | CC+rstack | Compression |
|-----------|-----------|-----------|-------------|
| Boilerplate | 2 days | 15 min | ~100x |
| Tests | 1 day | 15 min | ~50x |
| Feature | 1 week | 30 min | ~30x |
| Bug fix | 4 hours | 15 min | ~20x |

Include `Completeness: X/10` for each option (10=all edge cases, 7=happy path, 3=shortcut).

## Operational Feedback

Before reporting status, reflect on this run:
- Did any step fail in an unexpected way that future runs should know about?
- Did you discover a project-specific pattern, constraint, or quirk?
- Did a task take significantly longer than expected?

If yes, log it:
```bash
~/.rstack/bin/rstack-learnings-log '{"skill":"SKILL_NAME","type":"operational","key":"SHORT_KEY","insight":"DESCRIPTION","confidence":8,"source":"observed"}' 2>/dev/null || true
```

Only log genuine discoveries. A good test: would this insight save 5+ minutes in a future session?

## Completion Status Protocol

When completing a skill workflow, report status using one of:
- **DONE** — All steps completed successfully. Evidence provided for each claim.
- **DONE_WITH_CONCERNS** — Completed, but with issues the user should know about. List each concern.
- **BLOCKED** — Cannot proceed. State what is blocking and what was tried.
- **NEEDS_CONTEXT** — Missing information required to continue. State exactly what you need.

### Escalation

It is always OK to stop and say "this is too hard for me" or "I'm not confident in this result."

Bad work is worse than no work. You will not be penalized for escalating.
- If you have attempted a task 3 times without success, STOP and escalate.
- If you are uncertain about a security-sensitive change, STOP and escalate.
- If the scope of work exceeds what you can verify, STOP and escalate.

Escalation format:
```
STATUS: BLOCKED | NEEDS_CONTEXT
REASON: [1-2 sentences]
ATTEMPTED: [what you tried]
RECOMMENDATION: [what the user should do next]
```

## Quality Self-Check

Before reporting complete, verify:
- Does the skill complete its primary objective as described in the instructions?
- Is the output complete and verifiable?
- Would the user need to ask follow-up questions to get the value the skill promises?

If any answer is NO — fix it before closing the workflow.

## Telemetry (run last)

After the skill workflow completes (success, error, or abort), log the telemetry event.
Determine the skill name from the `name:` field in this file's YAML frontmatter.
Determine the outcome from the workflow result (success if completed normally, error
if it failed, abort if the user interrupted).

```bash
_TEL_END=$(date +%s)
_TEL_DUR=$(( _TEL_END - _TEL_START ))
if [ "${_TEL:-off}" != "off" ]; then
  echo '{"skill":"SKILL_NAME","duration_s":"'"$_TEL_DUR"'","outcome":"OUTCOME","session":"'"$_SESSION_ID"'","ts":"'$(date -u +%Y-%m-%dT%H:%M:%SZ)'"}' >> ~/.rstack/analytics/skill-usage.jsonl 2>/dev/null || true
fi
```

Replace `SKILL_NAME` with the actual skill name from frontmatter, `OUTCOME` with success/error/abort.

## Plan Status Footer

When you are in plan mode and about to call ExitPlanMode:

1. Check if the plan file already has a `## RSTACK REVIEW REPORT` section.
2. If it DOES — skip (a review skill already wrote a richer report).
3. If it does NOT — run this command:

\`\`\`bash
~/.rstack/bin/rstack-review-read
\`\`\`

Then write a `## RSTACK REVIEW REPORT` section to the end of the plan file.

If the output is `NO_REVIEWS` or empty, write this placeholder:

\`\`\`markdown
## RSTACK REVIEW REPORT

| Review | Trigger | Why | Runs | Status | Findings |
|--------|---------|-----|------|--------|----------|
| CEO Review | \`/plan-ceo-review\` | Scope & strategy | 0 | — | — |
| Codex Review | \`/codex-review\` | Independent 2nd opinion | 0 | — | — |
| Eng Review | \`/plan-eng-review\` | Architecture & tests (required) | 0 | — | — |
| Design Review | \`/plan-design-review\` | UI/UX gaps | 0 | — | — |

**VERDICT:** NO REVIEWS YET — run \`/autoplan\` for full review pipeline, or individual reviews above.
\`\`\`

**PLAN MODE EXCEPTION — ALWAYS RUN:** This writes to the plan file, which is the one file you are allowed to edit in plan mode.


# /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 Codex 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

## 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"` for git log queries — 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.

**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.

### Step 1: Gather Raw Data

First, fetch origin and identify the current user:
```bash
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):

```bash
# 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)
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/MR numbers from commit messages (GitHub #NNN, GitLab !NNN)
git log origin/<default> --since="<window>" --format="%s" | grep -oE '[#!][0-9]+' | sort -t'#' -k1 | uniq

# 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 ~/.rstack/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. gstack skill usage telemetry (if available)
cat ~/.rstack/analytics/skill-usage.jsonl 2>/dev/null || true

# 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 `~/.rstack/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.

**Skill Usage (if analytics exist):** Read `~/.rstack/analytics/skill-usage.jsonl` if it exists. Filter entries within the retro time window by `ts` field. Separate skill activations (no `event` field) from hook fires (`event: "hook_fire"`). Aggregate by skill name. Present as:

```
| Skill Usage | /ship(12) /qa(8) /review(5) · 3 safety hook fires |
```

If the JSONL file doesn't exist or has no entries in the window, skip the Skill Usage row.

**Eureka Moments (if logged):** Read `~/.rstack/analytics/eureka.jsonl` if it exists. Filter entries within the retro time window by `ts` field. For each eureka moment, show the skill that flagged it, the branch, and a one-line summary of the insight. Present as:

```
| Eureka Moments | 2 this period |
```

If 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"
```

If the JSONL file doesn't exist or has no entries in the window, skip the Eureka Moments row.

### Step 3: Commit Time Distribution

Show hourly histogram in local 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)

### 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., `noreply@anthropic.com`) but do not include them as team members — instead, track "AI-assisted commits" as a separate metric.

## Capture Learnings

If you discovered a non-obvious pattern, pitfall, or architectural insight during
this session, log it for future sessions:

```bash
~/.rstack/bin/rstack-learnings-log '{"skill":"retro","type":"TYPE","key":"SHORT_KEY","insight":"DESCRIPTION","confidence":N,"source":"SOURCE","files":["path/to/relevant/file"]}'
```

**Types:** `pattern` (reusable approach), `pitfall` (what NOT to do), `preference`
(user stated), `architecture` (structural decision), `tool` (library/framework insight).

**Sources:** `observed` (you found this in the code), `user-stated` (user told you),
`inferred` (AI deduction), `cross-model` (both Codex and Codex agree).

**Confidence:** 1-10. Be honest. An observed pattern you verified in the code is 8-9.
An inference you're not sure about is 4-5. A user preference they explicitly stated is 10.

**files:** Include the specific file paths this learning references. This enables
staleness detection: if those files are later deleted, the learning can be flagged.

**Only log genuine discoveries.** Don't log obvious things. Don't log things the user
already knows. A good test: would this insight save time in a future session? If yes, log it.

### 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/<default>, going back from today. Track both team streak and personal streak:

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

# Personal streak: only the current user's commits
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:

```bash
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:

```bash
mkdir -p .context/retros
```

Determine the next sequence number for today (substitute the actual date for `$(date +%Y-%m-%d)`):
```bash
setopt +o nomatch 2>/dev/null || true  # zsh compat
# Count existing retros for today to get next sequence number
today=$(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:
```json
{
  "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": {
    "Richardson Gunde": { "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 `~/.rstack/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 (command 10 returns > 0). If any has no data, omit the field entirely.

Include test health data in the JSON when test files exist:
```json
  "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:
```json
  "backlog": {
    "total_open": 28,
    "p0_p1": 2,
    "p2": 8,
    "completed_this_period": 3,
    "added_this_period": 1
  }
```

### Step 14: Write the Narrative

Structure the output as:

---

**Tweetable summary** (first line, before everything else):
```
Week of Mar 1: 47 commits (3 contributors), 3.2k LOC, 38% tests, 12 PRs, peak: 10pm | Streak: 47d
```

## Engineering Retro: [date range]

### Summary Table
(from Step 2)

### Trends vs Last Retro
(from Step 11, loaded before save — skip if first retro)

### Time & Session Patterns
(from Steps 3-4)

Narrative interpreting what the team-wide patterns mean:
- When the most productive hours are and what drives them
- Whether sessions are getting longer or shorter over time
- Estimated hours per day of active coding (team aggregate)
- Notable patterns: do team members code at the same time or in shifts?

### Shipping Velocity
(from Steps 5-7)

Narrative covering:
- Commit type mix and what it reveals
- PR size distribution and what it reveals about shipping cadence
- Fix-chain detection (sequences of fix commits on the same subsystem)
- Version bump discipline

### Code Quality Signals
- Test LOC ratio trend
- Hotspot analysis (are the same files churning?)
- Greptile signal ratio and trend (if history exists): "Greptile: X% signal (Y valid catches, Z false positives)"

### Test Health
- Total test files: N (from command 10)
- Tests added this period: M (from command 12 — test files changed)
- Regression test commits: list `test(qa):` and `test(design):` and `test: coverage` commits from command 11
- If prior retro exists and has `test_health`: show delta "Test count: {last} → {now} (+{delta})"
- If test ratio < 20%: flag as growth area — "100% test coverage is the goal. Tests make vibe coding safe."

### Plan Completion
Check review JSONL logs for plan completion data from /ship runs this period:

```bash
setopt +o nomatch 2>/dev/null || true  # zsh compat
eval "$(~/.rstack/bin/rstack-slug 2>/dev/null)"
cat ~/.rstack/projects/$SLUG/*-reviews.jsonl 2>/dev/null | grep '"skill":"ship"' | grep '"plan_items_total"' || echo "NO_PLAN_DATA"
```

If plan completion data exists within the retro time window:
- Count branches shipped with plans (entries that have `plan_items_total` > 0)
- Compute average completion: sum of `plan_items_done` / sum of `plan_items_total`
- Identify most-skipped item category if data supports it

Output:
```
Plan Completion This Period:
  {N} branches shipped with plans
  Average completion: {X}% ({done}/{total} items)
```

If no plan data exists, skip this section silently.

### Focus & Highlights
(from Step 8)
- Focus score with interpretation
- Ship of the week callout

### Your Week (personal deep-dive)
(from Step 9, for the current user only)

This is the section the user cares most about. Include:
- Their personal commit count, LOC, test ratio
- Their session patterns and peak hours
- Their focus areas
- Their biggest ship
- **What you did well** (2-3 specific things anchored in commits)
- **Where to level up** (1-2 specific, actionable suggestions)

### Team Breakdown
(from Step 9, for each teammate — skip if solo repo)

For each teammate (sorted by commits descending), write a section:

#### [Name]
- **What they shipped**: 2-3 sentences on their contributions, areas of focus, and commit patterns
- **Praise**: 1-2 specific things they did well, anchored in actual commits. Be genuine — what would you actually say in a 1:1? Examples:
  - "Cleaned up the entire auth module in 3 small, reviewable PRs — textbook decomposition"
  - "Added integration tests for every new endpoint, not just happy paths"
  - "Fixed the N+1 query that was causing 2s load times on the dashboard"
- **Opportunity for growth**: 1 specific, constructive suggestion. Frame as investment, not criticism. Examples:
  - "Test coverage on the payment module is at 8% — worth investing in before the next feature lands on top of it"
  - "Most commits land in a single burst — spacing work across the day could reduce context-switching fatigue"
  - "All commits land between 1-4am — sustainable pace matters for code quality long-term"

**AI collaboration note:** If many commits have `Co-Authored-By` AI trailers (e.g., Codex, Copilot), note the AI-assisted commit percentage as a team metric. Frame it neutrally — "N% of commits were AI-assisted" — without judgment.

### Top 3 Team Wins
Identify the 3 highest-impact things shipped in the window across the whole team. For each:
- What it was
- Who shipped it
- Why it matters (product/architecture impact)

### 3 Things to Improve
Specific, actionable, anchored in actual commits. Mix personal and team-level suggestions. Phrase as "to get even better, the team could..."

### 3 Habits for Next Week
Small, practical, realistic. Each must be something that takes <5 minutes to adopt. At least one should be team-oriented (e.g., "review each other's PRs same-day").

### Week-over-Week Trends
(if applicable, from Step 10)

---

## 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:

```bash
DISCOVER_BIN=""
[ -x ~/.rstack/bin/rstack-global-discover ] && DISCOVER_BIN=~/.rstack/bin/rstack-global-discover
[ -z "$DISCOVER_BIN" ] && [ -x .rstack/skills/gstack/bin/gstack-global-discover ] && DISCOVER_BIN=.rstack/skills/gstack/bin/gstack-global-discover
[ -z "$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:
```bash
$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:**

```bash
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.

```bash
# 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):

```bash
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, Codex 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:
- Codex: 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

```bash
setopt +o nomatch 2>/dev/null || true  # zsh compat
ls -t ~/.rstack/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

```bash
mkdir -p ~/.rstack/retros
```

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

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

```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": { "Codex": 15, "codex": 3, "gemini": 0 }
    }
  ],
  "totals": {
    "commits": 182,
    "insertions": 15300,
    "deletions": 4200,
    "projects": 5,
    "active_days": 6,
    "sessions": { "Codex": 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. Compute metrics 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, use `--since="2026-03-11T00:00:00"`)
2. Compute metrics 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: prior window is `--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.
- Use `origin/<default>` for all git queries (not local main which may be stale)
- Display all timestamps in the user's local timezone (do not override `TZ`)
- If the window has zero commits, say so and suggest a different window
- Round LOC/hour to nearest 50
- Treat merge commits as PR boundaries
- Do not read AGENTS.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 `~/.rstack/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".
