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memory-insights

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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.

AI Agents

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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