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@cloudkinetix/bmad-enhanced

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Cloud-Kinetix enhanced fork of BMAD-METHOD - Breakthrough Method of Agile AI-driven Development with robust versioning and unified validation.

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# Generate Learning Report ## Purpose Aggregate anonymous usage patterns from learning logs to create actionable insights. ## Context This task reads learning event logs and generates a comprehensive report showing usage patterns, friction points, and improvement opportunities. ## Input Required - None (reads from existing logs) ## Steps 1. **Check for learning logs** ```bash ls -la .bmad-workspace/ck-jira-integration/feedback/learning-log-*.md ``` 2. **Read and aggregate event data** - Count event types - Identify patterns - Calculate success rates - Find common friction points 3. **Generate aggregated report** File: `.bmad-workspace/ck-jira-integration/feedback/jira-expansion-learnings.md` Content structure: ```markdown # JIRA Expansion Pack - Usage Learnings Generated: {{date}} Sessions Analyzed: {{count}} ## Summary - Total events logged: {{event_count}} - Success rate: {{success_percentage}}% - Most common operations: {{top_3_operations}} - Average setup time: {{setup_time_range}} ## Observed Patterns ### Setup Experience - {{setup_success_rate}}% completed setup successfully - Common friction point: {{top_setup_issue}} - Most successful method: {{best_setup_approach}} ### Command Usage - Most confused commands: {{confused_commands}} - Help frequency: {{help_rate}} - Discovery patterns: {{how_users_find_features}} ### Sync Operations - Preview usage: {{preview_percentage}}% - Bulk sync adoption: {{bulk_usage}}% - Average items per sync: {{avg_sync_size}} ## Improvement Opportunities Based on usage patterns: 1. {{suggestion_1}} 2. {{suggestion_2}} 3. {{suggestion_3}} ## Anonymous Event Summary {{event_summary_table}} ``` 4. **Archive old logs** (optional) - Move logs older than 30 days to archive - Keep report current and relevant ## Output - Updated learning report at `.bmad-workspace/ck-jira-integration/feedback/jira-expansion-learnings.md` - Summary shown to user if requested ## Usage - Run periodically (weekly/monthly) - After significant usage (100+ events) - When user requests feedback summary - Before expansion pack updates ## Privacy Note All data remains anonymous and pattern-focused. No personal or project information is included in reports.