--- name: retrospective description: | Collect metrics from implementation batch reports and code review findings, analyze trends across cycles, and produce improvement reports with actionable recommendations. 3-step workflow: collect metrics, analyze trends, produce report. Outputs to _docs/06_metrics/. Trigger phrases: - "retrospective", "retro", "run retro" - "metrics review", "feedback loop" - "implementation metrics", "analyze trends" category: evolve tags: [retrospective, metrics, trends, improvement, feedback-loop] disable-model-invocation: true --- # Retrospective Collect metrics from implementation artifacts, analyze trends across development cycles, and produce actionable improvement reports. ## Core Principles - **Data-driven**: conclusions come from metrics, not impressions - **Actionable**: every finding must have a concrete improvement suggestion - **Cumulative**: each retrospective compares against previous ones to track progress - **Save immediately**: write artifacts to disk after each step - **Non-judgmental**: focus on process improvement, not blame ## Context Resolution Fixed paths: - IMPL_DIR: `_docs/03_implementation/` - METRICS_DIR: `_docs/06_metrics/` - TASKS_DIR: `_docs/02_tasks/` (scan all subfolders: `todo/`, `backlog/`, `done/`) Announce the resolved paths to the user before proceeding. ## Prerequisite Checks (BLOCKING) 1. `IMPL_DIR` exists and contains at least one `batch_*_report.md` — **STOP if missing** (nothing to analyze) 2. Create METRICS_DIR if it does not exist 3. Check for previous retrospective reports in METRICS_DIR to enable trend comparison ## Artifact Management ### Directory Structure ``` METRICS_DIR/ ├── retro_[YYYY-MM-DD].md ├── retro_[YYYY-MM-DD].md └── ... ``` ## Progress Tracking At the start of execution, create a TodoWrite with all steps (1 through 3). Update status as each step completes. ## Workflow ### Step 1: Collect Metrics **Role**: Data analyst **Goal**: Parse all implementation artifacts and extract quantitative metrics **Constraints**: Collection only — no interpretation yet #### Sources | Source | Metrics Extracted | |--------|------------------| | `batch_*_report.md` | Tasks per batch, batch count, task statuses (Done/Blocked/Partial) | | Code review sections in batch reports | PASS/FAIL/PASS_WITH_WARNINGS ratios, finding counts by severity and category | | Task spec files in TASKS_DIR | Complexity points per task, dependency count | | `FINAL_implementation_report.md` | Total tasks, total batches, overall duration | | Git log (if available) | Commits per batch, files changed per batch | #### Metrics to Compute **Implementation Metrics**: - Total tasks implemented - Total batches executed - Average tasks per batch - Average complexity points per batch - Total complexity points delivered **Quality Metrics**: - Code review pass rate (PASS / total reviews) - Code review findings by severity: Critical, High, Medium, Low counts - Code review findings by category: Bug, Spec-Gap, Security, Performance, Maintainability, Style, Scope - FAIL count (batches that required user intervention) **Efficiency Metrics**: - Blocked task count and reasons - Tasks completed on first attempt vs requiring fixes - Batch with most findings (identify problem areas) **Self-verification**: - [ ] All batch reports parsed - [ ] All metric categories computed - [ ] No batch reports missed --- ### Step 2: Analyze Trends **Role**: Process improvement analyst **Goal**: Identify patterns, recurring issues, and improvement opportunities **Constraints**: Analysis must be grounded in the metrics from Step 1 1. If previous retrospective reports exist in METRICS_DIR, load the most recent one for comparison 2. Identify patterns: - **Recurring findings**: which code review categories appear most frequently? - **Problem components**: which components/files generate the most findings? - **Complexity accuracy**: do high-complexity tasks actually produce more issues? - **Blocker patterns**: what types of blockers occur and can they be prevented? 3. Compare against previous retrospective (if exists): - Which metrics improved? - Which metrics degraded? - Were previous improvement actions effective? 4. Identify top 3 improvement actions ranked by impact **Self-verification**: - [ ] Patterns are grounded in specific metrics - [ ] Comparison with previous retro included (if exists) - [ ] Top 3 actions are concrete and actionable --- ### Step 3: Produce Report **Role**: Technical writer **Goal**: Write a structured retrospective report with metrics, trends, and recommendations **Constraints**: Concise, data-driven, actionable Write `METRICS_DIR/retro_[YYYY-MM-DD].md` using `templates/retrospective-report.md` as structure. **Self-verification**: - [ ] All metrics from Step 1 included - [ ] Trend analysis from Step 2 included - [ ] Top 3 improvement actions clearly stated - [ ] Suggested rule/skill updates are specific **Save action**: Write `retro_[YYYY-MM-DD].md` Present the report summary to the user. --- ## Escalation Rules | Situation | Action | |-----------|--------| | No batch reports exist | **STOP** — nothing to analyze | | Batch reports have inconsistent format | **WARN user**, extract what is available | | No previous retrospective for comparison | PROCEED — report baseline metrics only | | Metrics suggest systemic issue (>50% FAIL rate) | **WARN user** — suggest immediate process review | ## Methodology Quick Reference ``` ┌────────────────────────────────────────────────────────────────┐ │ Retrospective (3-Step Method) │ ├────────────────────────────────────────────────────────────────┤ │ PREREQ: batch reports exist in _docs/03_implementation/ │ │ │ │ 1. Collect Metrics → parse batch reports, compute metrics │ │ 2. Analyze Trends → patterns, comparison, improvement areas │ │ 3. Produce Report → _docs/06_metrics/retro_[date].md │ ├────────────────────────────────────────────────────────────────┤ │ Principles: Data-driven · Actionable · Cumulative │ │ Non-judgmental · Save immediately │ └────────────────────────────────────────────────────────────────┘ ```