본문으로 건너뛰기
cccskills
무료GitHub에 공개

gstack-openclaw-retro

Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware with per-person contributions, praise, and growth areas. Use when asked for weekly retro, what shipped this week, or engineering retrospective.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

연동 도구Telegram
설치 방법 보기

포함된 파일(1)

  • SKILL.md9.5 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

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.

Arguments

  • Default: last 7 days
  • 24h: last 24 hours
  • 14d: last 14 days
  • 30d: last 30 days
  • compare: compare current window vs prior same-length window

Instructions

Parse the argument to determine the time window. Default to 7 days. All times should be reported in the user's local timezone.

Midnight-aligned windows: For day units, compute an absolute start date at local midnight. 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. For hour units, use --since="N hours ago".


Step 1: Gather Raw Data

First, fetch origin and identify the current user:

git fetch origin main --quiet
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.

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

# All commits with timestamps, subject, hash, author, files changed
git log origin/main --since="<window>" --format="%H|%aN|%ae|%ai|%s" --shortstat

# Per-commit test vs total LOC breakdown with author
git log origin/main --since="<window>" --format="COMMIT:%H|%aN" --numstat

# Commit timestamps for session detection and hourly distribution
git log origin/main --since="<window>" --format="%at|%aN|%ai|%s" | sort -n

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

# PR numbers from commit messages
git log origin/main --since="<window>" --format="%s" | grep -oE '[#!][0-9]+' | sort -t'#' -k1 | uniq

# Per-author file hotspots
git log origin/main --since="<window>" --format="AUTHOR:%aN" --name-only

# Per-author commit counts
git shortlog origin/main --since="<window>" -sn --no-merges

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

# Test files changed in window
git log origin/main --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:

  • 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 → vX.Y.Z
  • Active days: N
  • Detected sessions: N
  • Avg LOC/session-hour: N

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


Step 3: Commit Time Distribution

Show hourly histogram in local time:

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

Identify:

  • Peak hours
  • Dead zones
  • Bimodal pattern (morning/evening) vs continuous
  • Late-night coding clusters (after 10pm)

Step 4: Work Session Detection

Detect sessions using 45-minute gap threshold between consecutive commits.

Classify sessions:

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

Calculate:

  • Total active coding time
  • 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% ... 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

Step 7: PR Size Distribution

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: Percentage of commits touching the single most-changed top-level directory. Higher = deeper focused work. Lower = scattered context-switching.

Ship of the week: The single highest-LOC PR in the window. Highlight PR number, LOC changed, and why it matters.


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 (peak hours), session count
  5. Test discipline ... their personal test LOC ratio
  6. Biggest ship ... their single highest-impact commit or PR

For the current user ("You"): Deepest treatment. Include all session analysis, time patterns, focus score. Frame in first person.

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

  • Praise (1-2 specific things): Anchor in actual commits. Not "great work" ... say exactly what was good.
  • Opportunity for growth (1 specific thing): Frame as leveling-up, not criticism. Anchor in actual data.

If solo repo: Skip team breakdown.

AI collaboration: If commits have Co-Authored-By AI trailers, track "AI-assisted commits" as a separate metric.


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

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, going back from today:

# Team streak
git log origin/main --format="%ad" --date=format:"%Y-%m-%d" | sort -u

# Personal streak
git log origin/main --author="<user_name>" --format="%ad" --date=format:"%Y-%m-%d" | sort -u

Display both:

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

Step 12: Load History & Compare

Check for prior retro history in memory/:

If prior retros exist, load the most recent one and calculate deltas:

                    Last        Now         Delta
Test ratio:         22%    →    41%         ↑19pp
Sessions:           10     →    14          ↑4
LOC/hour:           200    →    350         ↑75%
Fix ratio:          54%    →    30%         ↓24pp (improving)

If no prior retros exist, note "First retro recorded, run again next week to see trends."


Step 13: Save Retro History

Save a JSON snapshot to memory/retro-YYYY-MM-DD.json with metrics, authors, version range, streak, and tweetable summary.


Step 14: Write the Narrative

Format for Telegram (bullets, bold, no markdown tables in the final output).

Structure:

Tweetable summary (first line):

Week of Mar 1: 47 commits (3 contributors), 3.2k LOC, 38% tests, 12 PRs, peak: 10pm | Streak: 47d

Then sections:

  • Summary ... key metrics
  • Trends vs Last Retro ... deltas (skip if first retro)
  • Time & Session Patterns ... when the team codes, session lengths, deep vs micro
  • Shipping Velocity ... commit types, PR sizes, fix-chain detection
  • Code Quality Signals ... test ratio, hotspots, churn
  • Focus & Highlights ... focus score, ship of the week
  • Your Week ... personal deep-dive for the current user
  • Team Breakdown ... per-teammate analysis with praise + growth (skip if solo)
  • Top 3 Team Wins ... highest-impact things shipped
  • 3 Things to Improve ... specific, actionable, anchored in commits
  • 3 Habits for Next Week ... small, practical, realistic (<5 min to adopt)

Compare Mode

When the user says "compare":

  • Run the retro for the current window
  • Run the retro for the prior same-length window
  • Present side-by-side metrics with arrows showing improvement/regression
  • Brief narrative on biggest changes

Important Rules

  • All times in local timezone. Never set TZ.
  • Format for Telegram. Use bullets and bold. Avoid markdown tables in the final output.
  • Praise anchored in commits. Never say "great work" without naming what was good.
  • Growth areas anchored in data. Never criticize without evidence.
  • Save history. Every retro saves to memory/ for trend tracking.
  • Completion status:
    • DONE ... retro generated, history saved
    • DONE_WITH_CONCERNS ... generated but missing data (e.g., no prior retros for comparison)
    • BLOCKED ... not in a git repo or no commits in window

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," or "how long should I run this test." Use this whenever someone is comparing two approaches and wants to measure which performs better. For tracking implementation, see analytics-tracking. For page-level conversion optimization, see page-cro.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

mostafasudo/appilot32026년 9월 14일 업데이트

When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'ad iterations,' 'creative testing,' 'ad performance optimization,' 'write me some ads,' 'Facebook ad copy,' 'Google ad headlines,' 'LinkedIn ad text,' or 'I need more ad variations.' Use this whenever someone needs to produce ad copy at scale or iterate on existing ads. For campaign strategy and targeting, see paid-ads. For landing page copy, see copywriting.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

mostafasudo/appilot32026년 9월 14일 업데이트

ai-seo

무료

When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' or 'optimize for Claude/Gemini.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema-markup.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

mostafasudo/appilot32026년 9월 14일 업데이트

When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," "tracking plan," "how do I measure this," "track conversions," "attribution," "Mixpanel," "Segment," "are my events firing," or "analytics isn't working." Use this whenever someone asks how to know if something is working or wants to measure marketing results. For A/B test measurement, see ab-test-setup.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

mostafasudo/appilot32026년 9월 14일 업데이트

autoplan

무료

Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. Surfaces taste decisions (close approaches, borderline scope, codex disagreements) at a final approval gate. One command, fully reviewed plan out. Use when asked to "auto review", "autoplan", "run all reviews", "review this plan automatically", or "make the decisions for me". Proactively suggest when the user has a plan file and wants to run the full review gauntlet without answering 15-30 intermediate questions. (gstack) Voice triggers (speech-to-text aliases): "auto plan", "automatic review".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

mostafasudo/appilot32026년 9월 14일 업데이트

benchmark

무료

Performance regression detection using the browse daemon. Establishes baselines for page load times, Core Web Vitals, and resource sizes. Compares before/after on every PR. Tracks performance trends over time. Use when: "performance", "benchmark", "page speed", "lighthouse", "web vitals", "bundle size", "load time". (gstack) Voice triggers (speech-to-text aliases): "speed test", "check performance".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

mostafasudo/appilot32026년 9월 14일 업데이트

mostafasudo의 스킬 모두 보기

이 스킬의 문제 신고