engineering-retro
ProductivityGit-based engineering retrospective analyzing commits, PRs, and velocity over configurable windows with monorepo path scoping. Triggers on: "retrospective", "sprint retro", "weekly review", "what did we ship", "engineering retro", "dev summary", "commit analysis".
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Engineering Retrospective
Generate a structured, git-based engineering retrospective for a configurable time window. This is a read-only analysis — no files are modified except the optional JSON snapshot.
Arguments
/engineering-retro [TIME_WINDOW] [PATH_SCOPE]
- TIME_WINDOW (optional):
24h,7d(default),14d,30d - PATH_SCOPE (optional): restrict analysis to a subdirectory (monorepo support), e.g.
services/api
Examples:
/engineering-retro— last 7 days, full repo/engineering-retro 30d— last 30 days, full repo/engineering-retro 14d services/api— last 14 days, scoped toservices/api/
Execution Steps
Step 1: Environment Detection
Detect runtime context before any analysis:
# Default branch
DEFAULT_BRANCH=$(git symbolic-ref refs/remotes/origin/HEAD 2>/dev/null | sed 's@^refs/remotes/origin/@@')
if [ -z "$DEFAULT_BRANCH" ]; then
DEFAULT_BRANCH=$(git remote show origin 2>/dev/null | grep 'HEAD branch' | awk '{print $NF}')
fi
# System timezone
TZ_NAME=$(date +%Z)
# Time window — convert argument to --since format
# 24h → "24 hours ago", 7d → "7 days ago", 14d → "14 days ago", 30d → "30 days ago"
If DEFAULT_BRANCH detection fails, abort with an error — do not guess.
Step 2: Gather Raw Git Data
Collect commits within the time window on the detected default branch:
# All commits in window (with optional path scope)
git log origin/$DEFAULT_BRANCH --since="$SINCE" --format="%H|%aI|%aN|%s" -- $PATH_SCOPE
# Diff stats for the window
git log origin/$DEFAULT_BRANCH --since="$SINCE" --numstat --format="%H" -- $PATH_SCOPE
Capture: commit hash, author date (ISO), author name, subject line, files changed, insertions, deletions.
Step 3: Compute Aggregate Metrics
From the raw data, compute:
- Total commits in window
- Unique contributors (distinct author names)
- Files changed (unique file paths across all commits)
- Lines added (sum of insertions)
- Lines removed (sum of deletions)
- Net delta (added - removed)
- Avg commit size (total lines changed / total commits)
Step 4: Time Distribution
Analyze commit timestamps (converted to system timezone $TZ_NAME):
- Commits by day of week: Mon-Sun histogram
- Commits by hour: 0-23 histogram
- Peak day: day with most commits
- Peak hours: hours with most activity
Present as a compact text histogram.
Step 5: Session Analysis
Group commits into work sessions using a >2 hour gap as a session boundary:
- Sort commits by author and timestamp
- For each author, iterate chronologically — if gap between consecutive commits exceeds 2 hours, start a new session
- Compute per-session: duration (first commit to last commit), commit count
- Aggregate: total sessions, average session length, longest session, average commits per session
Sessions with a single commit get a default duration of 0 (point-in-time).
Step 6: Commit Type Classification
Classify each commit using conventional commit prefixes from the subject line:
| Prefix pattern | Category |
|---|---|
feat:, feat( | feature |
fix:, fix(, bugfix | fix |
refactor:, refactor( | refactor |
chore:, chore(, build:, ci: | chore |
docs:, doc: | docs |
test:, tests: | test |
perf: | perf |
style: | style |
For commits without conventional prefixes, apply diff heuristics:
- Primarily new files added → feature
- Primarily deletions → refactor
- Test files only → test
- Config/CI files only → chore
- Documentation files only → docs
- Otherwise → uncategorized
Report counts and percentages per category.
Step 7: Hotspot Analysis
Identify the top 10 most-modified files by number of commits touching them:
git log origin/$DEFAULT_BRANCH --since="$SINCE" --name-only --format="" -- $PATH_SCOPE | sort | uniq -c | sort -rn | head -20
Flag any file modified in >50% of total commits as a hotspot. Hotspots indicate:
- Active area of development (expected during feature work)
- Potential coupling issues (if unrelated commits keep touching the same file)
- Possible need for decomposition (if the file is large)
Step 8: PR Analysis
If the remote is GitHub (check git remote get-url origin for github.com):
# Merged PRs in window
gh pr list --state merged --base $DEFAULT_BRANCH --search "merged:>=$SINCE_DATE" --json number,title,author,mergedAt,additions,deletions,changedFiles,reviews
Compute:
- Total merged PRs
- Size distribution: S (<50 lines), M (50-200), L (200-500), XL (>500)
- Review turnaround: time from PR creation to first review (median, p90)
- Merge turnaround: time from PR creation to merge (median, p90)
If not a GitHub remote or gh is unavailable, skip this step and note it in the output.
Step 9: Focus Score
Compute the ratio of focused commits (touching 3 or fewer files) to total commits:
focus_score = commits_touching_le_3_files / total_commits
Interpretation:
- >0.8: highly focused, small incremental changes
- 0.5-0.8: moderate focus, mix of targeted and broad changes
- <0.5: broad changes dominating, may indicate large refactors or low commit discipline
Step 10: Per-Author Breakdown
For each contributor, report:
- Commit count
- Lines added / removed
- Top 3 most-touched files
- Primary commit types (from Step 6)
- Number of sessions and average session length (from Step 5)
Frame this as contributor highlights — recognition of work done, not a ranking or performance metric. Order alphabetically by author name.
Step 11: Week-over-Week Comparison
Check for a prior snapshot in .engineering-retros/:
- Find the most recent
*.jsonfile - If it exists and covers the adjacent prior window, compute deltas:
- Commit count delta (%)
- Lines changed delta (%)
- Contributor count delta
- Focus score delta
- Category distribution shift
If no prior snapshot exists, note this is the first retrospective and skip comparison.
Step 12: Save Snapshot
Save a JSON snapshot for future comparisons:
.engineering-retros/<YYYY-MM-DD>.json
Schema:
{
"date": "YYYY-MM-DD",
"window": "7d",
"path_scope": null,
"branch": "main",
"timezone": "PST",
"metrics": {
"commits": 0,
"contributors": 0,
"files_changed": 0,
"lines_added": 0,
"lines_removed": 0,
"net_delta": 0,
"focus_score": 0.0
},
"categories": {},
"hotspots": [],
"sessions": {
"total": 0,
"avg_length_minutes": 0
},
"authors": {},
"pr_stats": null
}
Create the .engineering-retros/ directory if it does not exist. Ensure .engineering-retros/ is in .gitignore (add it if missing — this is the one permitted file modification).
Step 13: Generate Narrative Summary
Produce the final output in this structure:
Engineering Retrospective — [DATE_RANGE] ([TIMEZONE]) Branch: [DEFAULT_BRANCH] | Scope: [PATH_SCOPE or "full repo"]
Metrics
- Commits: N | Contributors: N | Files changed: N
- Lines: +N / -N (net: +/-N)
- Avg commit size: N lines | Focus score: N.NN
Time Patterns
- Peak day: [DAY] | Peak hours: [RANGE]
- [compact histogram]
- Sessions: N total | Avg length: Nm | Longest: Nm
Work Breakdown
- [category]: N commits (NN%)
- ...
Hotspots
path/to/file— N commits [HOTSPOT if >50%]- ...
Contributor Highlights
- [Author]: N commits, +N/-N lines, focused on [top files], primarily [categories]
- ...
PR Summary (if available)
- Merged: N | Size dist: S/M/L/XL | Median review turnaround: Xh
Week-over-Week (if available)
- Commits: +/-N% | Lines: +/-N% | Focus: +/-N.NN
Observations
- [2-4 bullet points identifying patterns, achievements, and areas worth attention]
- Based on data only — no speculation about intent or quality judgments about individuals
Constraints
- Read-only: no code modifications, no branch changes, no git operations that alter state
- No hardcoded timezone: always detect from
date +%Z - No hardcoded branch: always detect dynamically via
git symbolic-reforgit remote show - No individual performance judgments: author breakdown is for recognition, not evaluation
- Path scope respected: all git commands must include
-- $PATH_SCOPEwhen a scope is provided - Snapshot storage:
.engineering-retros/only, never.context/retros/