auto-setup
Auto-detect project type and configure quality gates, permissions, and hooks for a new codebase
Surface patterns from your pro-workflow learnings and session history.
> /plugin marketplace add rohitg00/pro-workflow > /plugin install pro-workflow@pro-workflow
How it fires
How this command gets triggered: by you, by Claude, or both.
/insightsContext preview
What this command does when you run it.
Surface patterns from your pro-workflow learnings and session history.
Surface patterns from your pro-workflow learnings and session history.
/insights /insights session /insights learnings /insights corrections /insights heatmap
Current session stats:
Session Insights Duration: 47 min Edits: 23 files modified Corrections: 2 self-corrections applied Learnings: 3 new patterns captured Context: 62% used (safe)
Query the learnings database for patterns:
Learning Insights (42 total) Top categories: Testing 12 learnings (29%) Navigation 8 learnings (19%) Git 7 learnings (17%) Quality 6 learnings (14%) Editing 5 learnings (12%) Other 4 learnings (10%) Most applied: #12 [Testing] Run tests before commit — 15 times #8 [Navigation] Confirm path for common names — 11 times #23 [Git] Use feature branches always — 9 times Recent learnings (last 7 days): #42 [Claude-Code] Compact at task boundaries #41 [Prompting] Include acceptance criteria #40 [Architecture] Plan before multi-file edits Stale learnings (never applied): #15 [Editing] Prefer named exports — 0 times (45 days old) #19 [Context] Ask before large refactors — 0 times (30 days old)
Show what types of mistakes are recurring:
Correction Patterns Most corrected areas: File navigation 5 corrections Test coverage 3 corrections Commit messages 2 corrections Trend: Navigation errors decreasing (5 → 2 per week) Trend: Testing corrections stable (1 per week) Suggestions: - Add path confirmation rule to CLAUDE.md (3+ corrections) - Consider /learn-rule for test patterns
Show which files and patterns get corrected most across all sessions:
Correction Heatmap
By category (all time):
████████████ Testing 34 corrections
████████ Navigation 22 corrections
██████ Git 18 corrections
████ Quality 12 corrections
███ Editing 9 corrections
██ Architecture 6 corrections
By project:
my-api corrections_rate: 23% (high — review patterns)
my-frontend corrections_rate: 8% (healthy)
my-cli corrections_rate: 4% (excellent)
Adaptive quality gates:
Current threshold: 5 edits (tighter — 18% correction rate)
If rate drops below 15%: gates relax to 8 edits
If rate drops below 5%: gates relax to 10 edits
Hot learnings (most corrected, least learned):
- [Testing] Mock external dependencies — corrected 8x, learned 0x
→ Consider: /learn-rule to capture this permanently
- [Navigation] Check file exists before editing — corrected 5x, learned 1x
→ Pattern keeps recurring despite learning
Cold learnings (learned but never applied):
- [Editing] Use named exports — learned 45 days ago, applied 0x
→ Consider removing if no longer relevantProductivity (last 10 sessions) Avg session: 35 min Avg edits/session: 18 Correction rate: 12% (improving) Learning capture: 2.1 per session Best session: 2026-02-01 (28 edits, 0 corrections) Most productive hour: 10-11am
Run these SQLite queries against `~/.pro-workflow/data.db`:
**Heatmap by category:**
SELECT category, COUNT(*) as count FROM learnings WHERE mistake IS NOT NULL GROUP BY category ORDER BY count DESC
**Correction rate by project:**
SELECT project, SUM(corrections_count) as total_corrections, SUM(edit_count) as total_edits, ROUND(CAST(SUM(corrections_count) AS FLOAT) / NULLIF(SUM(edit_count), 0) * 100, 1) as rate FROM sessions WHERE project IS NOT NULL GROUP BY project ORDER BY rate DESC
**Hot learnings (most corrected patterns):**
SELECT category, rule, times_applied, (SELECT COUNT(*) FROM sessions WHERE corrections_count > 0) as correction_sessions FROM learnings WHERE mistake IS NOT NULL ORDER BY times_applied ASC, created_at ASC LIMIT 10
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**Trigger:** Use when user asks "show stats", "how am I doing", "what patterns", "analytics", "insights", "heatmap", "correction rate", or wants to understand their learning trajectory.
Claude Code learns from your corrections: self-correcting memory that compounds over 50+ sessions. Context engineering, parallel worktrees, agent teams, and 17 battle-tested skills.
Repo: rohitg00/pro-workflow
Auto-detect project type and configure quality gates, permissions, and hooks for a new codebase
Smart context compaction with state preservation — saves critical state before compact and restores after
Track session costs, understand token spend, and get optimization tips