Sprint Retrospective Expert The agent acts as a data-driven retrospective facilitator that mines git history, PR metadata, and commit patterns to generate comprehensive sprint retrospective reports. It goes beyond simple commit counts — analyzing velocity trends, contributor work patterns, code health indicators, and team collaboration dynamics to surface actionable insights. Keywords sprint retrospective, velocity analytics, contributor insights, code churn, work sessions, cycle time, lead time, throughput, burndown, team health, collaboration metrics, bus factor, refactor ratio, hotspot ana…

, clean)\n if tz_match:\n clean = clean[:tz_match.start()] + tz_match.group(1) + tz_match.group(2)\n try:\n return datetime.strptime(clean, \"%Y-%m-%dT%H:%M:%S%z\")\n except ValueError:\n pass\n # Try without timezone\n try:\n return datetime.strptime(clean[:19], \"%Y-%m-%dT%H:%M:%S\")\n except ValueError:\n pass\n # Last resort: try common date-only format\n try:\n return datetime.strptime(clean[:10], \"%Y-%m-%d\")\n except ValueError:\n return datetime.now()\n\n\ndef classify_commit_type(subject: str) -> str:\n \"\"\"Classify commit by conventional commit type.\"\"\"\n s = subject.lower().strip()\n prefixes = [\n (\"feat\", \"feat\"), (\"fix\", \"fix\"), (\"docs\", \"docs\"),\n (\"refactor\", \"refactor\"), (\"test\", \"test\"), (\"chore\", \"chore\"),\n (\"style\", \"style\"), (\"perf\", \"perf\"), (\"ci\", \"ci\"),\n (\"build\", \"build\"), (\"revert\", \"revert\"),\n ]\n for prefix, label in prefixes:\n if s.startswith(prefix + \":\") or s.startswith(prefix + \"(\"):\n return label\n return \"other\"\n\n\n# --- Session Detection ---\n\ndef detect_sessions(commits: list[dict], gap_minutes: int = 45) -> dict:\n \"\"\"Detect work sessions per author using gap threshold.\"\"\"\n by_author = defaultdict(list)\n for c in commits:\n dt = parse_datetime(c[\"date\"])\n by_author[c[\"author\"]].append(dt)\n\n sessions = {\"deep_work\": 0, \"focused\": 0, \"micro\": 0}\n all_sessions = []\n gap = timedelta(minutes=gap_minutes)\n\n for author, times in by_author.items():\n times.sort()\n if not times:\n continue\n session_start = times[0]\n session_end = times[0]\n\n for i in range(1, len(times)):\n if times[i] - session_end > gap:\n # Close previous session\n duration = (session_end - session_start).total_seconds() / 60\n all_sessions.append({\n \"author\": author,\n \"start\": session_start,\n \"end\": session_end,\n \"duration_min\": duration,\n })\n session_start = times[i]\n session_end = times[i]\n else:\n session_end = times[i]\n\n # Close final session\n duration = (session_end - session_start).total_seconds() / 60\n all_sessions.append({\n \"author\": author,\n \"start\": session_start,\n \"end\": session_end,\n \"duration_min\": duration,\n })\n\n for s in all_sessions:\n d = s[\"duration_min\"]\n if d > 50:\n sessions[\"deep_work\"] += 1\n elif d >= 20:\n sessions[\"focused\"] += 1\n else:\n sessions[\"micro\"] += 1\n\n return {\n \"deep_work\": sessions[\"deep_work\"],\n \"focused\": sessions[\"focused\"],\n \"micro\": sessions[\"micro\"],\n \"total\": len(all_sessions),\n \"details\": [\n {\n \"author\": s[\"author\"],\n \"start\": s[\"start\"].isoformat(),\n \"end\": s[\"end\"].isoformat(),\n \"duration_min\": round(s[\"duration_min\"], 1),\n \"type\": \"deep_work\" if s[\"duration_min\"] > 50 else (\"focused\" if s[\"duration_min\"] >= 20 else \"micro\"),\n }\n for s in all_sessions\n ],\n }\n\n\n# --- Hourly Distribution ---\n\ndef hourly_distribution(commits: list[dict]) -> dict[int, int]:\n \"\"\"Count commits by hour of day.\"\"\"\n hours = defaultdict(int)\n for c in commits:\n dt = parse_datetime(c[\"date\"])\n hours[dt.hour] += 1\n return dict(sorted(hours.items()))\n\n\n# --- Cycle Time Estimation ---\n\ndef estimate_cycle_time(merges: list[dict], commits: list[dict], repo: str = \".\") -> float:\n \"\"\"Estimate average cycle time (hours) from branch commits to merge.\"\"\"\n if not merges:\n return 0.0\n cycle_times = []\n commit_dates = {c[\"hash\"]: parse_datetime(c[\"date\"]) for c in commits}\n\n for m in merges:\n merge_dt = parse_datetime(m[\"date\"])\n # Get commits in the merge\n parents = run_git([\"log\", \"--pretty=format:%H|%aI\", f\"{m['hash']}^..{m['hash']}\", \"--no-merges\"], repo)\n if not parents:\n continue\n earliest = merge_dt\n for line in parents.split(\"\\n\"):\n parts = line.split(\"|\", 1)\n if len(parts) \u003c 2:\n continue\n cdt = parse_datetime(parts[1])\n if cdt \u003c earliest:\n earliest = cdt\n if earliest \u003c merge_dt:\n hours = (merge_dt - earliest).total_seconds() / 3600\n if hours > 0:\n cycle_times.append(hours)\n\n if not cycle_times:\n return 0.0\n return sum(cycle_times) / len(cycle_times)\n\n\n# --- Main Analysis ---\n\ndef analyze_period(since: str, until: str, repo: str, gap_minutes: int) -> dict:\n \"\"\"Run full velocity analysis for a time period.\"\"\"\n commits = get_commits(since, until, repo)\n merges = get_merge_commits(since, until, repo)\n loc = get_loc_stats(since, until, repo)\n pr_sizes = get_pr_loc_stats(merges, repo)\n\n # Parse date range for day count\n try:\n d_since = datetime.strptime(since, \"%Y-%m-%d\")\n d_until = datetime.strptime(until, \"%Y-%m-%d\")\n days = max((d_until - d_since).days, 1)\n except ValueError:\n days = 7\n\n # Commit type breakdown\n type_counts = defaultdict(int)\n for c in commits:\n t = classify_commit_type(c[\"subject\"])\n type_counts[t] += 1\n\n # Sessions\n sessions = detect_sessions(commits, gap_minutes)\n\n # Hourly\n hourly = hourly_distribution(commits)\n\n # Cycle time\n cycle_time = estimate_cycle_time(merges, commits, repo)\n\n # PR metrics\n avg_pr_size = int(round(sum(pr_sizes) / len(pr_sizes))) if pr_sizes else 0\n throughput = round(len(commits) / days, 1) if days > 0 else 0\n deploy_freq = round(len(merges) / days, 1) if days > 0 else 0\n\n # Unique authors\n authors = list(set(c[\"author\"] for c in commits))\n\n return {\n \"period\": {\"since\": since, \"until\": until, \"days\": days},\n \"total_commits\": len(commits),\n \"total_merges\": len(merges),\n \"loc\": loc,\n \"avg_pr_size_loc\": int(avg_pr_size),\n \"throughput_per_day\": throughput,\n \"cycle_time_hours\": round(cycle_time, 1),\n \"deploy_frequency_per_day\": deploy_freq,\n \"commit_types\": dict(sorted(type_counts.items(), key=lambda x: -x[1])),\n \"hourly_distribution\": hourly,\n \"sessions\": {\n \"deep_work\": sessions[\"deep_work\"],\n \"focused\": sessions[\"focused\"],\n \"micro\": sessions[\"micro\"],\n \"total\": sessions[\"total\"],\n },\n \"unique_authors\": authors,\n \"author_count\": len(authors),\n }\n\n\n# --- Comparison ---\n\ndef compute_delta(current: float, previous: float) -> str:\n \"\"\"Compute percentage delta with direction indicator.\"\"\"\n if previous == 0:\n return \"N/A\"\n pct = ((current - previous) / previous) * 100\n arrow = \"+\" if pct >= 0 else \"\"\n return f\"{arrow}{pct:.0f}%\"\n\n\ndef compare_periods(current: dict, previous: dict) -> dict:\n \"\"\"Compare two period analyses and produce deltas.\"\"\"\n deltas = {}\n compare_keys = [\n (\"total_commits\", \"Commits\"),\n (\"total_merges\", \"PRs Merged\"),\n (\"throughput_per_day\", \"Throughput\"),\n (\"cycle_time_hours\", \"Cycle Time\"),\n (\"deploy_frequency_per_day\", \"Deploy Frequency\"),\n (\"avg_pr_size_loc\", \"Avg PR Size\"),\n ]\n for key, label in compare_keys:\n cur = current.get(key, 0)\n prev = previous.get(key, 0)\n deltas[label] = {\n \"current\": cur,\n \"previous\": prev,\n \"delta\": compute_delta(cur, prev),\n }\n # LOC comparison\n deltas[\"LOC Net\"] = {\n \"current\": current.get(\"loc\", {}).get(\"net\", 0),\n \"previous\": previous.get(\"loc\", {}).get(\"net\", 0),\n \"delta\": compute_delta(\n current.get(\"loc\", {}).get(\"net\", 0),\n previous.get(\"loc\", {}).get(\"net\", 0)\n ),\n }\n return deltas\n\n\n# --- Text Formatting ---\n\ndef bar_chart(value: int, max_value: int, width: int = 20) -> str:\n \"\"\"Create a simple text bar chart.\"\"\"\n if max_value == 0:\n return \" \" * width\n filled = round((value / max_value) * width)\n filled = min(filled, width)\n return \"\\u2588\" * filled + \"\\u2591\" * (width - filled)\n\n\ndef format_text(data: dict, comparison: dict | None = None) -> str:\n \"\"\"Format velocity data as human-readable text.\"\"\"\n p = data[\"period\"]\n lines = [\n f\"Sprint Velocity Report ({p['since']} to {p['until']})\",\n \"=\" * 55,\n \"\",\n ]\n\n # Summary metrics\n if comparison:\n lines.append(f\"{'Metric':\u003c25} {'Current':>10} {'Previous':>10} {'Delta':>10}\")\n lines.append(\"-\" * 55)\n for label, vals in comparison.items():\n cur = vals[\"current\"]\n prev = vals[\"previous\"]\n delta = vals[\"delta\"]\n lines.append(f\"{label:\u003c25} {str(cur):>10} {str(prev):>10} {delta:>10}\")\n else:\n lines.append(f\" Throughput: {data['throughput_per_day']} commits/day\")\n lines.append(f\" LOC Net: {data['loc']['net']:+,} lines (added: {data['loc']['added']:,}, removed: {data['loc']['removed']:,})\")\n lines.append(f\" PRs Merged: {data['total_merges']}\")\n lines.append(f\" Avg PR Size: {data['avg_pr_size_loc']} LOC\")\n lines.append(f\" Cycle Time: {data['cycle_time_hours']} hours\")\n lines.append(f\" Deploy Frequency: {data['deploy_frequency_per_day']}/day\")\n lines.append(f\" Unique Authors: {data['author_count']}\")\n\n # Commit types\n lines.extend([\"\", \"Commit Types:\", \"-\" * 40])\n ct = data.get(\"commit_types\", {})\n max_ct = max(ct.values()) if ct else 1\n total_ct = sum(ct.values()) if ct else 1\n for ctype, count in sorted(ct.items(), key=lambda x: -x[1]):\n pct = round(count / total_ct * 100) if total_ct else 0\n lines.append(f\" {ctype:\u003c12} {bar_chart(count, max_ct)} {pct:>3}% ({count})\")\n\n # Hourly distribution\n lines.extend([\"\", \"Hourly Activity:\", \"-\" * 40])\n hourly = data.get(\"hourly_distribution\", {})\n max_h = max(hourly.values()) if hourly else 1\n for hour in range(24):\n count = hourly.get(hour, 0)\n if count > 0:\n lines.append(f\" {hour:02d}:00 {bar_chart(count, max_h, 30)} {count}\")\n\n # Sessions\n s = data.get(\"sessions\", {})\n total_s = s.get(\"total\", 0) or 1\n lines.extend([\"\", \"Work Sessions:\", \"-\" * 40])\n lines.append(f\" Deep Work (>50min): {s.get('deep_work', 0):>4} ({round(s.get('deep_work', 0)/total_s*100)}%)\")\n lines.append(f\" Focused (20-50min): {s.get('focused', 0):>4} ({round(s.get('focused', 0)/total_s*100)}%)\")\n lines.append(f\" Micro (\u003c20min): {s.get('micro', 0):>4} ({round(s.get('micro', 0)/total_s*100)}%)\")\n lines.append(f\" Total Sessions: {s.get('total', 0):>4}\")\n\n return \"\\n\".join(lines)\n\n\n# --- CLI ---\n\ndef parse_args() -> argparse.Namespace:\n parser = argparse.ArgumentParser(\n description=\"Sprint Velocity Analyzer — analyze git history for velocity metrics\"\n )\n parser.add_argument(\"--days\", type=int, default=7,\n help=\"Number of days to analyze (default: 7)\")\n parser.add_argument(\"--since\", type=str, default=None,\n help=\"Start date (YYYY-MM-DD), overrides --days\")\n parser.add_argument(\"--until\", type=str, default=None,\n help=\"End date (YYYY-MM-DD), defaults to today\")\n parser.add_argument(\"--compare-previous\", action=\"store_true\",\n help=\"Compare against the previous period of equal length\")\n parser.add_argument(\"--gap-minutes\", type=int, default=45,\n help=\"Session gap threshold in minutes (default: 45)\")\n parser.add_argument(\"--repo\", type=str, default=\".\",\n help=\"Path to git repository (default: current directory)\")\n parser.add_argument(\"-f\", \"--format\", choices=[\"text\", \"json\"], default=\"text\",\n help=\"Output format (default: text)\")\n return parser.parse_args()\n\n\ndef main():\n args = parse_args()\n\n # Determine date range\n if args.until:\n until_date = args.until\n else:\n until_date = datetime.now().strftime(\"%Y-%m-%d\")\n\n if args.since:\n since_date = args.since\n try:\n d_since = datetime.strptime(since_date, \"%Y-%m-%d\")\n d_until = datetime.strptime(until_date, \"%Y-%m-%d\")\n days = (d_until - d_since).days\n except ValueError:\n days = args.days\n else:\n days = args.days\n d_until = datetime.strptime(until_date, \"%Y-%m-%d\")\n d_since = d_until - timedelta(days=days)\n since_date = d_since.strftime(\"%Y-%m-%d\")\n\n # Validate repo\n check = run_git([\"rev-parse\", \"--is-inside-work-tree\"], args.repo)\n if check != \"true\":\n print(f\"Error: '{args.repo}' is not a git repository.\", file=sys.stderr)\n sys.exit(1)\n\n # Analyze current period\n current = analyze_period(since_date, until_date, args.repo, args.gap_minutes)\n\n # Optionally analyze previous period\n comparison = None\n previous = None\n if args.compare_previous:\n prev_until = since_date\n prev_since = (d_since - timedelta(days=days)).strftime(\"%Y-%m-%d\")\n previous = analyze_period(prev_since, prev_until, args.repo, args.gap_minutes)\n comparison = compare_periods(current, previous)\n\n # Output\n if args.format == \"json\":\n output = {\"current\": current}\n if comparison:\n output[\"previous\"] = previous\n output[\"comparison\"] = comparison\n print(json.dumps(output, indent=2, default=str))\n else:\n print(format_text(current, comparison))\n\n\nif __name__ == \"__main__\":\n main()\n","content_type":"text/x-python; charset=utf-8","language":"python","size":18414,"content_sha256":"e5c3a3e4b6b39ffdcc9aec89a5bb84338377f49a8eebd48cefc7662e7af11d68"}],"content_json":{"type":"doc","content":[{"type":"heading","attrs":{"level":1},"content":[{"text":"Sprint Retrospective Expert","type":"text"}]},{"type":"paragraph","content":[{"text":"The agent acts as a data-driven retrospective facilitator that mines git history, PR metadata, and commit patterns to generate comprehensive sprint retrospective reports. It goes beyond simple commit counts — analyzing velocity trends, contributor work patterns, code health indicators, and team collaboration dynamics to surface actionable insights.","type":"text"}]},{"type":"heading","attrs":{"level":2},"content":[{"text":"Keywords","type":"text"}]},{"type":"paragraph","content":[{"text":"sprint retrospective, velocity analytics, contributor insights, code churn, work sessions, cycle time, lead time, throughput, burndown, team health, collaboration metrics, bus factor, refactor ratio, hotspot analysis, conventional commits, session detection, deep work, improvement tracking","type":"text"}]},{"type":"heading","attrs":{"level":2},"content":[{"text":"Quick Start","type":"text"}]},{"type":"code_block","attrs":{"wrap":false,"language":"bash"},"content":[{"text":"# 1. Sprint velocity analysis (last 14 days)\npython scripts/velocity_analyzer.py --days 14 --format json > velocity.json\n\n# 2. Contributor deep dive\npython scripts/contributor_insights.py --days 14 --format json > contributors.json\n\n# 3. Code churn analysis\npython scripts/code_churn_analyzer.py --days 14 --format json > churn.json\n\n# 4. Generate full retrospective report\npython scripts/retro_report_generator.py \\\n --velocity velocity.json \\\n --contributors contributors.json \\\n --churn churn.json \\\n --sprint-name \"Sprint 23\" \\\n --output retro_sprint_23.md\n\n# One-liner: full pipeline\npython scripts/velocity_analyzer.py --days 14 -f json > /tmp/v.json && \\\npython scripts/contributor_insights.py --days 14 -f json > /tmp/c.json && \\\npython scripts/code_churn_analyzer.py --days 14 -f json > /tmp/ch.json && \\\npython scripts/retro_report_generator.py -v /tmp/v.json -c /tmp/c.json -u /tmp/ch.json -s \"Sprint 23\"","type":"text"}]},{"type":"heading","attrs":{"level":2},"content":[{"text":"Core Workflows","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"1. Sprint Velocity Analysis","type":"text"}]},{"type":"paragraph","content":[{"text":"Analyze throughput, cycle time, and delivery patterns across the sprint window.","type":"text"}]},{"type":"code_block","attrs":{"wrap":false,"language":"bash"},"content":[{"text":"# Default: last 7 days\npython scripts/velocity_analyzer.py\n\n# Custom range\npython scripts/velocity_analyzer.py --since 2026-03-04 --until 2026-03-18\n\n# Compare against previous period\npython scripts/velocity_analyzer.py --days 14 --compare-previous\n\n# JSON output for pipeline\npython scripts/velocity_analyzer.py --days 14 --format json","type":"text"}]},{"type":"paragraph","content":[{"text":"Metrics computed:","type":"text","marks":[{"type":"strong"}]}]},{"type":"table","attrs":{"layout":null},"content":[{"type":"tr","content":[{"type":"th","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Metric","type":"text"}]}]},{"type":"th","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Description","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Total Commits","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Raw commit count in window","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"LOC Added / Removed / Net","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Lines of code delta","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"PRs Merged","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Pull requests merged (via merge commit detection)","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Avg PR Size","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Average lines changed per PR","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Throughput","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Commits per day","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Cycle Time","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Avg time from first commit on branch to merge","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Lead Time","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Avg time from commit to production (main branch)","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Deploy Frequency","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Merges to main per day","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Commit Type Breakdown","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"feat/fix/docs/refactor/test/chore distribution","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Hourly Distribution","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Commit activity by hour of day","type":"text"}]}]}]}]},{"type":"paragraph","content":[{"text":"Session Detection:","type":"text","marks":[{"type":"strong"}]}]},{"type":"paragraph","content":[{"text":"The analyzer detects work sessions using configurable gap thresholds:","type":"text"}]},{"type":"table","attrs":{"layout":null},"content":[{"type":"tr","content":[{"type":"th","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Session Type","type":"text"}]}]},{"type":"th","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Duration","type":"text"}]}]},{"type":"th","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Interpretation","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Deep Work","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":">50 min","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Sustained focused coding","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Focused","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"20-50 min","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Standard development sessions","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Micro","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"\u003c20 min","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Quick fixes, reviews, hotfixes","type":"text"}]}]}]}]},{"type":"paragraph","content":[{"text":"Gap threshold default: 45 minutes. Commits within the gap belong to the same session.","type":"text"}]},{"type":"paragraph","content":[{"text":"Trend Comparison:","type":"text","marks":[{"type":"strong"}]}]},{"type":"paragraph","content":[{"text":"When ","type":"text"},{"text":"--compare-previous","type":"text","marks":[{"type":"code_inline"}]},{"text":" is enabled, the tool compares the current window against the immediately preceding window of equal length and computes deltas with directional indicators.","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"2. 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frequent changes — coordination overhead","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Cross-boundary work","type":"text","marks":[{"type":"strong"}]},{"text":": Commits spanning multiple directories — integration work","type":"text"}]}]}]},{"type":"heading","attrs":{"level":2},"content":[{"text":"State Persistence & Trend Tracking","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Snapshot Storage","type":"text"}]},{"type":"paragraph","content":[{"text":"Save retro data after each sprint for historical comparison:","type":"text"}]},{"type":"code_block","attrs":{"wrap":false,"language":"bash"},"content":[{"text":"# Save sprint snapshot (auto-names by sprint)\npython scripts/retro_report_generator.py -v velocity.json -c contributors.json -u churn.json \\\n -s \"Sprint 23\" --save .retro-history/\n\n# Compare two sprints\npython scripts/retro_report_generator.py -v velocity.json -c contributors.json -u churn.json \\\n -s \"Sprint 24\" --previous-velocity .retro-history/sprint-23-velocity.json","type":"text"}]},{"type":"paragraph","content":[{"text":"Storage:","type":"text","marks":[{"type":"strong"}]},{"text":" ","type":"text"},{"text":".retro-history/{sprint-name}-{type}.json","type":"text","marks":[{"type":"code_inline"}]},{"text":" — velocity, contributors, churn snapshots per sprint.","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Trend Analysis","type":"text"}]},{"type":"paragraph","content":[{"text":"After 3+ sprints, the report generator includes:","type":"text"}]},{"type":"bullet_list","content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Velocity trajectory","type":"text","marks":[{"type":"strong"}]},{"text":" — throughput and cycle time trending up, down, or stable","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Sprint-over-sprint deltas","type":"text","marks":[{"type":"strong"}]},{"text":" — percentage changes with directional indicators","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Streak tracking","type":"text","marks":[{"type":"strong"}]},{"text":" — consecutive sprints with improving velocity, shrinking cycle time, or growing test ratio","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Attention alerts","type":"text","marks":[{"type":"strong"}]},{"text":" — categories that degraded 3+ sprints in a row","type":"text"}]}]}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Action Item Carry-Over","type":"text"}]},{"type":"paragraph","content":[{"text":"The report generator parses previous retro reports for unchecked action items:","type":"text"}]},{"type":"bullet_list","content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Scans ","type":"text"},{"text":"- [ ]","type":"text","marks":[{"type":"code_inline"}]},{"text":" checkboxes in prior ","type":"text"},{"text":".retro-history/","type":"text","marks":[{"type":"code_inline"}]},{"text":" markdown files","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Carries forward incomplete items into the new report's \"Outstanding Actions\" section","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Tracks completion rate: \"3 of 5 action items from Sprint 22 completed (60%)\"","type":"text"}]}]}]},{"type":"hr","attrs":{"markup":"---"}},{"type":"heading","attrs":{"level":2},"content":[{"text":"Narrative Generation Guidelines","type":"text"}]},{"type":"paragraph","content":[{"text":"A retrospective report is not a data dump — it tells the story of the sprint.","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Structure","type":"text"}]},{"type":"ordered_list","attrs":{"order":1,"listStyle":"number"},"content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Tweetable summary","type":"text","marks":[{"type":"strong"}]},{"text":" (1 sentence) — the sprint in a tweet. Example: \"Sprint 24 shipped 42 commits with +8K LOC, closing 3 epics — highest feat velocity this quarter, but cycle time crept up 15%.\"","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Executive summary","type":"text","marks":[{"type":"strong"}]},{"text":" (2-3 sentences) — data-driven, actionable, no filler","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Velocity dashboard","type":"text","marks":[{"type":"strong"}]},{"text":" — metrics table with deltas vs previous","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Commit type distribution","type":"text","marks":[{"type":"strong"}]},{"text":" — ASCII bar chart","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Work session analysis","type":"text","marks":[{"type":"strong"}]},{"text":" — deep/focused/micro breakdown with implications","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Contributor spotlights","type":"text","marks":[{"type":"strong"}]},{"text":" — per-person metrics, specialization, peak hours","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Code health indicators","type":"text","marks":[{"type":"strong"}]},{"text":" — churn rate, hotspots, test ratio, refactor frequency","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Action items","type":"text","marks":[{"type":"strong"}]},{"text":" — 3-5 specific, measurable improvements for next sprint","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Outstanding actions","type":"text","marks":[{"type":"strong"}]},{"text":" — carry-over from previous retros","type":"text"}]}]}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Tone Guidelines","type":"text"}]},{"type":"bullet_list","content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Celebratory for wins","type":"text","marks":[{"type":"strong"}]},{"text":" — \"Highest feature velocity in 4 sprints\" not \"Feature velocity increased\"","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Constructive for improvements","type":"text","marks":[{"type":"strong"}]},{"text":" — \"Cycle time crept up, suggesting review bottleneck\" not \"Cycle time is bad\"","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Never blame-oriented","type":"text","marks":[{"type":"strong"}]},{"text":" — Frame around systems and processes, not individuals","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Data-dense","type":"text","marks":[{"type":"strong"}]},{"text":" — Every claim backed by a specific number. No \"we shipped a lot\" — say \"42 commits, +8,247 LOC\"","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Word count target","type":"text","marks":[{"type":"strong"}]},{"text":" — 1500-3000 words for a full report. Enough depth to be actionable, short enough to be read.","type":"text"}]}]}]},{"type":"hr","attrs":{"markup":"---"}},{"type":"heading","attrs":{"level":2},"content":[{"text":"Integration Points","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"With Scrum Master Skill (","type":"text"},{"text":"project-management/scrum-master/","type":"text","marks":[{"type":"code_inline"}]},{"text":")","type":"text"}]},{"type":"code_block","attrs":{"wrap":false,"language":"bash"},"content":[{"text":"# Use scrum-master capacity data alongside retro velocity\npython scripts/velocity_analyzer.py --repo . --days 14 -f json > velocity.json\n# Cross-reference with sprint capacity planning\npython ../scrum-master/scripts/sprint_capacity_calculator.py team.json","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"With Senior PM Skill (","type":"text"},{"text":"project-management/senior-pm/","type":"text","marks":[{"type":"code_inline"}]},{"text":")","type":"text"}]},{"type":"code_block","attrs":{"wrap":false,"language":"bash"},"content":[{"text":"# Feed retro insights into stakeholder reports\npython scripts/retro_report_generator.py -v velocity.json -c contributors.json -u churn.json -s \"Sprint 24\" -o retro.md\n# Reference in PM executive reporting via senior-pm stakeholder tools","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"With Delivery Manager Skill (","type":"text"},{"text":"project-management/delivery-manager/","type":"text","marks":[{"type":"code_inline"}]},{"text":")","type":"text"}]},{"type":"code_block","attrs":{"wrap":false,"language":"bash"},"content":[{"text":"# Retro metrics inform release planning\n# Velocity trends help delivery managers forecast sprint capacity\npython scripts/velocity_analyzer.py --days 30 --compare-previous -f json","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"With Agile Coach Skill (","type":"text"},{"text":"project-management/agile-coach/","type":"text","marks":[{"type":"code_inline"}]},{"text":")","type":"text"}]},{"type":"paragraph","content":[{"text":"The agile coach uses retro trend data to identify systemic patterns:","type":"text"}]},{"type":"bullet_list","content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Declining deep work sessions → suggest focus time blocks","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Rising cycle time → investigate review process","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Low test ratio → recommend TDD adoption sprint","type":"text"}]}]}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"CI/CD Integration","type":"text"}]},{"type":"code_block","attrs":{"wrap":false,"language":"yaml"},"content":[{"text":"# .github/workflows/sprint-retro.yml\nname: Sprint Retrospective\non:\n schedule:\n - cron: '0 9 * * 5' # Every Friday at 9am\n workflow_dispatch:\n inputs:\n days:\n description: 'Sprint length in days'\n default: '14'\njobs:\n retrospective:\n runs-on: ubuntu-latest\n steps:\n - uses: actions/checkout@v4\n with:\n fetch-depth: 0\n - run: |\n python scripts/velocity_analyzer.py --days ${{ inputs.days || '14' }} -f json > velocity.json\n python scripts/contributor_insights.py --days ${{ inputs.days || '14' }} -f json > contributors.json\n python scripts/code_churn_analyzer.py --days ${{ inputs.days || '14' }} -f json > churn.json\n python scripts/retro_report_generator.py -v velocity.json -c contributors.json -u churn.json -s \"Sprint $(date +%V)\"","type":"text"}]},{"type":"hr","attrs":{"markup":"---"}},{"type":"heading","attrs":{"level":2},"content":[{"text":"Retrospective Facilitation","type":"text"}]},{"type":"paragraph","content":[{"text":"See ","type":"text"},{"text":"references/retrospective_facilitation.md","type":"text","marks":[{"type":"code_inline"}]},{"text":" for:","type":"text"}]},{"type":"bullet_list","content":[{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"8 retrospective formats (Start/Stop/Continue, 4Ls, Sailboat, DAKI, etc.)","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Facilitation techniques for remote and in-person teams","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Anti-patterns to avoid (blame game, scope creep, no follow-through)","type":"text"}]}]},{"type":"list_item","content":[{"type":"paragraph","content":[{"text":"Psychological safety frameworks","type":"text"}]}]}]},{"type":"hr","attrs":{"markup":"---"}},{"type":"heading","attrs":{"level":2},"content":[{"text":"Output Examples","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Velocity Dashboard","type":"text"}]},{"type":"code_block","attrs":{"wrap":false,"language":""},"content":[{"text":"Sprint Velocity Report — Sprint 24 (Mar 4-18, 2026)\n═══════════════════════════════════════════════════════\n\nThroughput: 8.2 commits/day (↑ 12% vs prev)\nLOC Net: +2,847 lines (↓ 5% vs prev)\nPRs Merged: 14 (↑ 17% vs prev)\nAvg PR Size: 203 lines (↓ 8% — smaller PRs!)\nCycle Time: 18.3 hours (↑ 2h — review bottleneck?)\nDeploy Frequency: 1.0/day (stable)\n\nCommit Types:\n feat ████████████░░░░░░░░ 42%\n fix ██████░░░░░░░░░░░░░░ 18%\n docs ████░░░░░░░░░░░░░░░░ 14%\n refactor ███░░░░░░░░░░░░░░░░░ 12%\n test ██░░░░░░░░░░░░░░░░░░ 8%\n chore ██░░░░░░░░░░░░░░░░░░ 6%","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Contributor Spotlight","type":"text"}]},{"type":"code_block","attrs":{"wrap":false,"language":""},"content":[{"text":"Contributor: [email protected]\n Commits: 34 | LOC: +1,204 / -387 | Files: 28\n Sessions: 12 (deep: 5, focused: 4, micro: 3)\n Peak Hours: 10am-12pm, 2pm-4pm\n Specialization: Backend (67%), Tests (22%), Docs (11%)\n Consistency: 0.82 (highly consistent)","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Code Churn Analysis","type":"text"}]},{"type":"code_block","attrs":{"wrap":false,"language":""},"content":[{"text":"File Hotspots (ranked by churn score)\n─────────────────────────────────────────────────\n File Chg Auth Score\n ───────────────────────────── ──── ──── ──────\n src/api/routes.ts 12 3 11.2 ██████████\n src/models/user.ts 8 2 7.4 ███████░░░\n README.md 7 1 5.8 █████░░░░░\n\nRefactoring Candidates:\n src/api/routes.ts — high churn (0.8/day), 3 authors, consider splitting","type":"text"}]},{"type":"heading","attrs":{"level":3},"content":[{"text":"Full Report (generated by pipeline)","type":"text"}]},{"type":"code_block","attrs":{"wrap":false,"language":"markdown"},"content":[{"text":"# Sprint Retrospective — Sprint 24\n\n> Sprint 24 shipped 42 commits with +2.8K LOC across 14 PRs — strongest\n> feature velocity this quarter, but cycle time crept up 15% suggesting\n> a review bottleneck.\n\n## Executive Summary\nThis sprint delivered 42 commits across 3 contributors, merging 14 PRs\nwith a net change of +2,847 lines. Feature work dominated at 42% of commits.\nCycle time increased to 18.3 hours (+2h vs Sprint 23), correlating with\nlarger average PR sizes in the auth migration epic.\n\n## Velocity Dashboard\n| Metric | Sprint 24 | Sprint 23 | Delta |\n|-----------------|-----------|-----------|---------|\n| Commits | 42 | 38 | +10.5% |\n| LOC Net | +2,847 | +2,996 | -5.0% |\n| PRs Merged | 14 | 12 | +16.7% |\n| Cycle Time | 18.3h | 16.1h | +13.7% |\n\n## Action Items\n- [ ] Investigate review bottleneck — cycle time up 2h\n- [ ] Split src/api/routes.ts — highest churn file (12 changes)\n- [ ] Increase test ratio — currently 0.08, target 0.15","type":"text"}]},{"type":"hr","attrs":{"markup":"---"}},{"type":"heading","attrs":{"level":2},"content":[{"text":"Troubleshooting","type":"text"}]},{"type":"table","attrs":{"layout":null},"content":[{"type":"tr","content":[{"type":"th","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Symptom","type":"text"}]}]},{"type":"th","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Likely Cause","type":"text"}]}]},{"type":"th","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Resolution","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"velocity_analyzer.py returns zero commits","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Wrong date range, repo not fetched with full history, or branch filter excluding commits","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Verify ","type":"text"},{"text":"--since","type":"text","marks":[{"type":"code_inline"}]},{"text":"/","type":"text"},{"text":"--until","type":"text","marks":[{"type":"code_inline"}]},{"text":" dates; ensure ","type":"text"},{"text":"git fetch --all","type":"text","marks":[{"type":"code_inline"}]},{"text":" was run; check ","type":"text"},{"text":"--repo","type":"text","marks":[{"type":"code_inline"}]},{"text":" path points to a valid git repo","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Session detection shows 100% micro sessions","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Session gap threshold too low, or all commits are atomic (one-line changes)","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Increase ","type":"text"},{"text":"--gap-minutes","type":"text","marks":[{"type":"code_inline"}]},{"text":" from 45 to 60-90; micro-heavy patterns may genuinely indicate context-switching","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Contributor specialization shows \"other\" for all files","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"File extensions not matching any SPECIALIZATION_PATTERNS category","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Check if your codebase uses non-standard extensions; the tool classifies by extension and path patterns","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Code churn hotspots dominated by generated files","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Auto-generated files (lock files, builds, migrations) inflate churn scores","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Use ","type":"text"},{"text":"--path src/","type":"text","marks":[{"type":"code_inline"}]},{"text":" to filter to source code, or add generated file patterns to .gitignore","type":"text"}]}]}]},{"type":"tr","content":[{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Retro report generator produces empty sections","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Input JSON files contain ","type":"text"},{"text":"{}","type":"text","marks":[{"type":"code_inline"}]},{"text":" or data keys do not match expected schema","type":"text"}]}]},{"type":"td","attrs":{"colspan":1,"rowspan":1,"colwidth":null,"alignment":""},"content":[{"type":"paragraph","content":[{"text":"Verify velocity JSON has ","type":"text"},{"text":"total_commits","type":"text","marks":[{"type":"code_inline"}]},{"text":", ","type":"text"},{"text":"loc","type":"text","marks":[{"type":"code_inline"}]},{"text":", ","type":"text"},{"text":"sessions","type":"text","marks":[{"type":"code_inline"}]},{"text":" keys; 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Sprint Retrospective Expert The agent acts as a data-driven retrospective facilitator that mines git history, PR metadata, and commit patterns to generate comprehensive sprint retrospective reports. It goes beyond simple commit counts — analyzing velocity trends, contributor work patterns, code health indicators, and team collaboration dynamics to surface actionable insights. Keywords sprint retrospective, velocity analytics, contributor insights, code churn, work sessions, cycle time, lead time, throughput, burndown, team health, collaboration metrics, bus factor, refactor ratio, hotspot ana…