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feat(retro): absorb inline git/awk metrics into bin/gstack-retro-metrics + carve report format
RETRO_METRICS_PROTO: 1 contract, local git reads only (fetch stays in the skill prose), degraded path documented in the skeleton. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
Garry Tan
co-authored by
Claude Fable 5
Claude Fable 5
parent
b007814be0
commit
e0250aa128
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{
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"$schema": "https://gstack.dev/schemas/section-manifest.json",
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"skill": "retro",
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"version": 1,
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"note": "PASSIVE registry (v2 plan T9 / CM2). id/file/title/trigger text ONLY. The skeleton's decision-tree prose decides WHEN to read. No machine predicate here.",
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"sections": [
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{
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"id": "report-format",
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"file": "report-format.md",
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"title": "Narrative report structure — tweetable summary, section-by-section output template, Test Health, Plan Completion, personal deep-dive, team breakdown, wins/improvements/habits (Step 14)",
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"trigger": "writing the retrospective narrative (Step 14, after all metrics are computed and compared)"
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}
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]
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}
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<!-- AUTO-GENERATED from report-format.md.tmpl — do not edit directly -->
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<!-- Regenerate: bun run gen:skill-docs -->
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Structure the output as:
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---
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**Tweetable summary** (first line, before everything else):
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```
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Week of Mar 1: 47 commits (3 contributors), 3.2k LOC, 38% tests, 12 PRs, peak: 10pm | Streak: 47d
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```
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## Engineering Retro: [date range]
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### Summary Table
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(from Step 2)
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### Trends vs Last Retro
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(from Step 12, loaded before save — skip if first retro)
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### Time & Session Patterns
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(from Steps 3-4)
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Narrative interpreting what the team-wide patterns mean:
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- When the most productive hours are and what drives them
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- Whether sessions are getting longer or shorter over time
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- Estimated hours per day of active coding (team aggregate)
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- Notable patterns: do team members code at the same time or in shifts?
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### Shipping Velocity
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(from Steps 5-7)
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Narrative covering:
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- Commit type mix and what it reveals
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- PR size distribution and what it reveals about shipping cadence
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- Fix-chain detection (sequences of fix commits on the same subsystem)
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- Version bump discipline
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### Code Quality Signals
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- Test LOC ratio trend
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- Hotspot analysis (are the same files churning?)
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- Greptile signal ratio and trend (if history exists): "Greptile: X% signal (Y valid catches, Z false positives)"
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### Test Health
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- Total test files: N (`TEST_FILES_TOTAL`)
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- Tests added this period: M (`TEST_FILES_CHANGED` — test files changed in the window)
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- Regression test commits: list the `REGRESSION_COMMIT` lines (`test(qa):`, `test(design):`, and `test: coverage` commits)
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- If prior retro exists and has `test_health`: show delta "Test count: {last} → {now} (+{delta})"
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- If test ratio < 20%: flag as growth area — "100% test coverage is the goal. Tests make vibe coding safe."
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### Plan Completion
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Check review JSONL logs for plan completion data from /ship runs this period:
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```bash
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setopt +o nomatch 2>/dev/null || true # zsh compat
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eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)"
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cat ~/.gstack/projects/$SLUG/*-reviews.jsonl 2>/dev/null | grep '"skill":"ship"' | grep '"plan_items_total"' || echo "NO_PLAN_DATA"
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```
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If plan completion data exists within the retro time window:
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- Count branches shipped with plans (entries that have `plan_items_total` > 0)
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- Compute average completion: sum of `plan_items_done` / sum of `plan_items_total`
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- Identify most-skipped item category if data supports it
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Output:
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```
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Plan Completion This Period:
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{N} branches shipped with plans
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Average completion: {X}% ({done}/{total} items)
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```
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If no plan data exists, skip this section silently.
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### Focus & Highlights
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(from Step 8)
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- Focus score with interpretation
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- Ship of the week callout
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### Your Week (personal deep-dive)
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(from Step 9, for the current user only)
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This is the section the user cares most about. Include:
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- Their personal commit count, LOC, test ratio
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- Their session patterns and peak hours
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- Their focus areas
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- Their biggest ship
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- **What you did well** (2-3 specific things anchored in commits)
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- **Where to level up** (1-2 specific, actionable suggestions)
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### Team Breakdown
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(from Step 9, for each teammate — skip if solo repo)
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For each teammate (sorted by commits descending), write a section:
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#### [Name]
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- **What they shipped**: 2-3 sentences on their contributions, areas of focus, and commit patterns
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- **Praise**: 1-2 specific things they did well, anchored in actual commits. Be genuine — what would you actually say in a 1:1? Examples:
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- "Cleaned up the entire auth module in 3 small, reviewable PRs — textbook decomposition"
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- "Added integration tests for every new endpoint, not just happy paths"
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- "Fixed the N+1 query that was causing 2s load times on the dashboard"
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- **Opportunity for growth**: 1 specific, constructive suggestion. Frame as investment, not criticism. Examples:
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- "Test coverage on the payment module is at 8% — worth investing in before the next feature lands on top of it"
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- "Most commits land in a single burst — spacing work across the day could reduce context-switching fatigue"
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- "All commits land between 1-4am — sustainable pace matters for code quality long-term"
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**AI collaboration note:** If many commits have `Co-Authored-By` AI trailers (e.g., Claude, Copilot), note the AI-assisted commit percentage as a team metric. Frame it neutrally — "N% of commits were AI-assisted" — without judgment.
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### Top 3 Team Wins
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Identify the 3 highest-impact things shipped in the window across the whole team. For each:
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- What it was
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- Who shipped it
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- Why it matters (product/architecture impact)
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### 3 Things to Improve
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Specific, actionable, anchored in actual commits. Mix personal and team-level suggestions. Phrase as "to get even better, the team could..."
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### 3 Habits for Next Week
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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").
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### Week-over-Week Trends
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(if applicable, from Step 10)
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@@ -0,0 +1,118 @@
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Structure the output as:
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---
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**Tweetable summary** (first line, before everything else):
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```
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Week of Mar 1: 47 commits (3 contributors), 3.2k LOC, 38% tests, 12 PRs, peak: 10pm | Streak: 47d
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```
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## Engineering Retro: [date range]
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### Summary Table
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(from Step 2)
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### Trends vs Last Retro
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(from Step 12, loaded before save — skip if first retro)
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### Time & Session Patterns
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(from Steps 3-4)
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Narrative interpreting what the team-wide patterns mean:
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- When the most productive hours are and what drives them
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- Whether sessions are getting longer or shorter over time
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- Estimated hours per day of active coding (team aggregate)
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- Notable patterns: do team members code at the same time or in shifts?
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### Shipping Velocity
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(from Steps 5-7)
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Narrative covering:
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- Commit type mix and what it reveals
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- PR size distribution and what it reveals about shipping cadence
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- Fix-chain detection (sequences of fix commits on the same subsystem)
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- Version bump discipline
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### Code Quality Signals
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- Test LOC ratio trend
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- Hotspot analysis (are the same files churning?)
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- Greptile signal ratio and trend (if history exists): "Greptile: X% signal (Y valid catches, Z false positives)"
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### Test Health
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- Total test files: N (`TEST_FILES_TOTAL`)
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- Tests added this period: M (`TEST_FILES_CHANGED` — test files changed in the window)
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- Regression test commits: list the `REGRESSION_COMMIT` lines (`test(qa):`, `test(design):`, and `test: coverage` commits)
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- If prior retro exists and has `test_health`: show delta "Test count: {last} → {now} (+{delta})"
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- If test ratio < 20%: flag as growth area — "100% test coverage is the goal. Tests make vibe coding safe."
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### Plan Completion
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Check review JSONL logs for plan completion data from /ship runs this period:
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```bash
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setopt +o nomatch 2>/dev/null || true # zsh compat
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eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)"
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cat ~/.gstack/projects/$SLUG/*-reviews.jsonl 2>/dev/null | grep '"skill":"ship"' | grep '"plan_items_total"' || echo "NO_PLAN_DATA"
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```
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If plan completion data exists within the retro time window:
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- Count branches shipped with plans (entries that have `plan_items_total` > 0)
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- Compute average completion: sum of `plan_items_done` / sum of `plan_items_total`
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- Identify most-skipped item category if data supports it
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Output:
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```
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Plan Completion This Period:
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{N} branches shipped with plans
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Average completion: {X}% ({done}/{total} items)
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```
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If no plan data exists, skip this section silently.
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### Focus & Highlights
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(from Step 8)
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- Focus score with interpretation
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- Ship of the week callout
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### Your Week (personal deep-dive)
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(from Step 9, for the current user only)
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This is the section the user cares most about. Include:
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- Their personal commit count, LOC, test ratio
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- Their session patterns and peak hours
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- Their focus areas
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- Their biggest ship
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- **What you did well** (2-3 specific things anchored in commits)
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- **Where to level up** (1-2 specific, actionable suggestions)
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### Team Breakdown
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(from Step 9, for each teammate — skip if solo repo)
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For each teammate (sorted by commits descending), write a section:
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#### [Name]
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- **What they shipped**: 2-3 sentences on their contributions, areas of focus, and commit patterns
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- **Praise**: 1-2 specific things they did well, anchored in actual commits. Be genuine — what would you actually say in a 1:1? Examples:
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- "Cleaned up the entire auth module in 3 small, reviewable PRs — textbook decomposition"
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- "Added integration tests for every new endpoint, not just happy paths"
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- "Fixed the N+1 query that was causing 2s load times on the dashboard"
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- **Opportunity for growth**: 1 specific, constructive suggestion. Frame as investment, not criticism. Examples:
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- "Test coverage on the payment module is at 8% — worth investing in before the next feature lands on top of it"
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- "Most commits land in a single burst — spacing work across the day could reduce context-switching fatigue"
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- "All commits land between 1-4am — sustainable pace matters for code quality long-term"
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**AI collaboration note:** If many commits have `Co-Authored-By` AI trailers (e.g., Claude, Copilot), note the AI-assisted commit percentage as a team metric. Frame it neutrally — "N% of commits were AI-assisted" — without judgment.
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||||
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### Top 3 Team Wins
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Identify the 3 highest-impact things shipped in the window across the whole team. For each:
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- What it was
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- Who shipped it
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- Why it matters (product/architecture impact)
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### 3 Things to Improve
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Specific, actionable, anchored in actual commits. Mix personal and team-level suggestions. Phrase as "to get even better, the team could..."
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### 3 Habits for Next Week
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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").
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### Week-over-Week Trends
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(if applicable, from Step 10)
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Reference in New Issue
Block a user