Add .cursor autodevelopment system
6.7 KiB
name, description, category, tags, disable-model-invocation
| name | description | category | tags | disable-model-invocation | |||||
|---|---|---|---|---|---|---|---|---|---|
| retrospective | 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" | evolve |
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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/
Announce the resolved paths to the user before proceeding.
Prerequisite Checks (BLOCKING)
IMPL_DIRexists and contains at least onebatch_*_report.md— STOP if missing (nothing to analyze)- Create METRICS_DIR if it does not exist
- 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
- If previous retrospective reports exist in METRICS_DIR, load the most recent one for comparison
- 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?
- Compare against previous retrospective (if exists):
- Which metrics improved?
- Which metrics degraded?
- Were previous improvement actions effective?
- 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 │
└────────────────────────────────────────────────────────────────┘