memory-insights
Analyze session friction trends, success rates, and satisfaction patterns across sessions using Claude Code facets data. Read-only query tool for on-demand trend analysis.
What this skill does
# Memory Insights — Session Trend Analysis Read-only analytics over Claude Code facets data for friction trends, success patterns, and satisfaction signals. ## Data Source Read all JSON files in `~/.claude/usage-data/facets/` (skip gracefully if directory doesn't exist). Each file is a per-session analysis with fields: `session_id`, `underlying_goal`, `goal_categories`, `outcome`, `session_type`, `claude_helpfulness`, `primary_success`, `friction_counts`, `friction_detail`, `user_satisfaction_counts`, `brief_summary`. **Graceful degradation:** If `~/.claude/usage-data/facets/` doesn't exist, output: "No facets data available. Facets are generated by Claude Code and may not be present on all installations. Session insights require at least one completed Claude Code session." ## Commands ### Default (no arguments): Summary Dashboard Show a summary dashboard: - Total sessions analyzed: [N] - Outcome breakdown: fully_achieved [N], mostly_achieved [N], etc. - Helpfulness: essential [N], very_helpful [N], etc. - Top 5 friction types with counts - Sessions with friction: [N]/[total] ([%]) - Satisfaction: [satisfied+likely_satisfied] positive, [dissatisfied+frustrated] negative ### /memory-insights friction — Friction Deep Dive - All friction types ranked by count - Top 5 highest-friction sessions with brief_summary and friction_detail - Correlation: which goal_categories have the most friction? - Trend: is friction increasing or decreasing over recent sessions? ### /memory-insights sessions --worst — Highest-Friction Sessions - Sort all sessions by total friction count (descending) - Show top 10 with: session_id, brief_summary, friction_counts, outcome - Include friction_detail for each ### /memory-insights sessions --best — Most Successful Sessions - Filter: outcome=fully_achieved AND friction_counts is empty - Show with: session_id, brief_summary, primary_success, session_type ### /memory-insights patterns — Cross-Session Pattern Analysis - Correlate friction types with goal_categories (e.g., "wrong_approach clusters around debugging and configuration_change tasks") - Correlate session_type with outcome (e.g., "iterative_refinement has 80% fully_achieved vs multi_task at 50%") - Identify which primary_success factors appear in friction-free sessions ## Privacy Facets data contains session summaries and goals but no file contents. No privacy tag filtering is needed. However, do not expose full `underlying_goal` text if it might contain sensitive project details — summarize instead. ## Insight Routing After presenting analysis results, check if findings represent actionable conventions that should be preserved for future sessions. Examples of routable insights: - "Debugging tasks have 100% friction rate" → friction.md convention - "Docker/container tasks fail consistently" → friction.md convention - "Iterative refinement sessions spiral after 3 attempts" → friction.md convention Present proposed additions: > Insights suggest adding to friction.md: > - "When debugging, verify hypothesis before fix attempts (2-strike limit)" > <!-- @category: pattern --> > Route to friction.md? [y/n] On approval, write to `.claude/memory/friction.md`. If the file doesn't exist, create it with a `# Friction Patterns` header and `## Conventions` / `## Project-Specific` sections (same template as `/memory-init`). Cap total entries at ~15-20. If file exceeds cap after adding new entries, drop the least-recurrent entries (those without repeated evidence across multiple sessions).
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