learning-analyzer

> **AI-consumed reference.** Optimized for Claude to read during execution. > Human-readable explanation: see [docs/architecture/HIERARCHICAL_PLANNING.md](../../../docs/architecture/HIERARCHICAL_PLANNING.md) > or [docs/getting-started/](../../../docs/getting-started/) depending on topic. # Learning Analyzer Skill Analyze learning data from Supabase: success/failure patterns, optimization opportunities, agent performance. --- ## Usage ```bash /af learn analyze # Full analysis /af learn analyze --period 30d # Last 30 days /af learn analyze --focus agents # Agent performance /af learn analyze --focus workflows # Workflow patterns /af learn analyze --focus feedback # User feedback ``` --- ## Process ### 1. Query Supabase Views ```toon views[5]{view,purpose}: v_agent_success_rates,Agent performance by task type v_common_patterns,Identified patterns v_improvement_suggestions,Actionable suggestions v_workflow_trends,Weekly workflow trends v_feedback_summary,Feedback statistics ``` ### 2. AI Pattern Recognition Identify: Top 3 success patterns, top 3 failure patterns, top 3 optimization opportunities, agent recommendations. ### 3. Output Report ```markdown ## Learning Analysis Report Generated: {timestamp} | Period: {dates} ### Success Patterns 1. **Pattern:** {description} — Frequency: {N}, Confidence: {%} ### Failure Patterns 1. **Pattern:** {description} — Impact: {severity}, Suggested Fix: {fix} ### Optimization...