insights

$npx mdskill add rohitg00/pro-workflow/insights

Show session analytics and learning patterns for improved productivity

  • Identifies user coding activities and learns from past interactions to suggest improvements.
  • Deploys machine learning algorithms on project history and real-time activity data.
  • Analyzes corrections and learnings to provide actionable insights and recommendations.
  • Delivers summarized analytics through a dashboard for easy monitoring of productivity.

SKILL.md

.github/skills/insightsView on GitHub ↗
---
name: insights
description: Show session analytics, learning patterns, correction trends, heatmaps, and productivity metrics. Computes stats from project memory and session history. Use when asking for stats, statistics, progress, how am I doing, coding history, or dashboard.
user-invocable: true
---

# Session Insights

Surface patterns from learnings and session history.

## Trigger

Use when asking "show stats", "how am I doing", "analytics", "insights", "heatmap", or "correction rate".

## Data Sources

Gather data from these locations before computing metrics:

```bash
# Session history and learnings
cat .claude/LEARNED.md 2>/dev/null || cat CLAUDE.md | grep -A999 "LEARNED"
cat .claude/learning-log.md 2>/dev/null

# Session activity
git log --oneline --since="today" --author="$(git config user.name)"
git diff --stat
```

A **correction** is any instance where the user redirected, fixed, or overrode agent output during a session. Count `[LEARN]` entries and explicit correction markers in session history.

## What It Shows

### Session Summary

```
Session Insights
  Duration: 47 min
  Edits: 23 files modified
  Corrections: 2 self-corrections applied
  Learnings: 3 new patterns captured
  Context: 62% used (safe)
```

### Learning Analytics

```
Learning Insights (42 total)

Top categories:
  Testing     12 learnings (29%)
  Navigation   8 learnings (19%)
  Git          7 learnings (17%)
  Quality      6 learnings (14%)

Most applied:
  #12 [Testing] Run tests before commit — 15 times
  #8  [Navigation] Confirm path for common names — 11 times

Stale learnings (never applied):
  #15 [Editing] Prefer named exports — 0 times (45 days old)
```

### Correction Heatmap

```
Correction Heatmap

By category (all time):
  ████████████ Testing      34 corrections
  ████████     Navigation   22 corrections
  ██████       Git          18 corrections
  ████         Quality      12 corrections

Hot learnings (most corrected, least learned):
  - [Testing] Mock external deps — corrected 8x, learned 0x
    → Consider: /learn-rule to capture this permanently

Cold learnings (learned but never applied):
  - [Editing] Use named exports — learned 45 days ago, applied 0x
    → Consider removing if no longer relevant
```

### Productivity Metrics

```
Productivity (last 10 sessions)
  Avg session: 35 min
  Avg edits/session: 18
  Correction rate: 12% (improving)
  Learning capture: 2.1 per session
```

## Guardrails

- Use actual data from project memory and session history.
- Surface actionable suggestions, not just numbers.
- Flag recurring corrections that should become permanent rules.
- Identify stale learnings that may no longer be relevant.

## Output

Formatted analytics report with:
- Current session stats
- Category breakdown
- Most/least applied learnings
- Correction trends with suggestions
- Productivity metrics over time

More from rohitg00/pro-workflow

SkillDescription
agent-teamsCoordinate multiple Claude Code sessions as a team — lead + teammates with shared task lists, mailbox messaging, and file-lock claiming. Patterns for team sizing, task decomposition, and when to use teams vs sub-agents vs worktrees.
auto-setupAuto-configure quality gates, hooks, and settings for a new project. Detects project type and sets up appropriate tooling. Use when onboarding a new codebase.
batch-orchestrationDecompose large-scale changes into independent units and spawn parallel agents in isolated worktrees. Use for migrations, refactors, codemods, and any change touching 10+ files with the same pattern.
bug-captureCapture a user-reported defect as a durable GitHub issue written in the project's own domain language. Explores the codebase in parallel for context but never leaks file paths or line numbers into the issue. Use when the user reports a bug conversationally, runs a QA pass, or says "file an issue", "log this as a bug", "capture this".
compact-guardSmart context compaction with state preservation. Saves critical files, task progress, and working state before compaction, restores after. Use before manual compact or when auto-compact triggers.
context-optimizerOptimize token usage and context management. Use when sessions feel slow, context is degraded, or you're running out of budget.
cost-trackerTrack session costs, set budget alerts, and optimize token spend. Use to check costs mid-session or set spending limits.
design-engineeringApply interface craft when building or reviewing UI - motion, easing, timing, springs, component feel, and visual foundations. Use when building a component, animation, transition, hover or press state, modal, drawer, toast, or when polishing an interface so it feels right. Says "make this feel better", "add an animation", "polish the UI", "review this component".
deslopRemove AI-generated code slop, unnecessary comments, and over-engineering from the current branch diff. Cleans up boilerplate, simplifies abstractions, strips defensive code, and in skill-file mode lints SKILL.md files for quality. Use when cleaning up code, simplifying, removing boilerplate, before committing, or when reviewing a skill before promoting it.
domain-modelingBuild the project's shared language and bounded contexts before writing code, so names stay consistent and the agent stops paraphrasing domain concepts. Produces a CONTEXT.md glossary and decision records. Use at the start of a project or feature, or when the codebase and the people describing it speak different languages.