Skip to main content

/pm-skill-discover

Detect workflow patterns from AI sessions and suggest reusable skills.

What It Does​

Analyzes your recent AI development sessions to detect repeated workflow patterns and suggests new skills you could create to automate them. Includes:

  • Claude Code session transcript analysis (tool usage patterns)
  • Git history analysis (file-group patterns, commit frequency)
  • jaan-to learning file analysis (skill usage frequency)
  • 4-dimension scoring rubric (frequency, time saved, parameterizability, risk)
  • Matching against 10 known workflow archetypes from research
  • Optional auto-invocation of /skill-create for selected patterns

Usage​

/pm-skill-discover
/pm-skill-discover --days=7
/pm-skill-discover --days=30 --min-frequency=5 --max-suggestions=3

Parameters​

FlagDefaultDescription
--days=N14Number of days to analyze
--min-frequency=N3Minimum pattern occurrences to surface
--max-suggestions=N5Maximum suggestions to present

Data Sources​

SourceWhat It Extracts
Claude Code sessionsTool names, result status, timestamps (structural metadata only)
Git historyFile groups, commit frequency, message categories
jaan-to learn filesSkill usage frequency, accumulated lesson counts

Privacy: Only structural metadata is extracted. No raw code, prompts, file paths, or variable values are stored or displayed.

Scoring Rubric​

Each candidate pattern is scored on 4 dimensions:

DimensionWeightWhat It Measures
Frequency30%How often the pattern occurs per week
Time Saved30%Estimated duration x frequency
Parameterizability25%Ratio of variable to fixed steps
Risk15%Inverse of destructive operations

Patterns scoring above 40/100 are surfaced as candidates.

Known Archetypes​

Detected patterns are matched against 10 research-backed workflow archetypes:

  1. Error diagnosis and fix cycle
  2. Red-green-refactor loop
  3. CI pipeline repair
  4. Dependency update workflow
  5. Code review response pattern
  6. Feature scaffolding
  7. Migration execution
  8. API integration
  9. Merge conflict resolution
  10. Post-deployment verification

Output​

Path: jaan-to/outputs/pm/skill-discover/{id}-{slug}/{id}-{slug}.md

Contains:

  • Executive summary with total estimated time savings
  • Data source statistics
  • Discovered patterns with full scoring breakdown
  • Archetype matches
  • Pre-filled /skill-create commands for each candidate

Example​

Input:

/pm-skill-discover --days=14

Preview at HARD STOP:

SKILL DISCOVERY REPORT
══════════════════════
Period: 14 days | Sessions: 23 | Episodes: 67
Patterns detected: 12 | Above threshold: 3

TOP SUGGESTIONS
───────────────
1. [Score: 87] "Error Diagnosis Cycle"
   Frequency: 12x/week | Est. savings: ~40 min/week
   Archetype: Error diagnosis and fix cycle
   Suggested skill: qa-error-fix

2. [Score: 72] "Feature File Scaffolding"
   Frequency: 5x/week | Est. savings: ~25 min/week
   Archetype: Feature scaffolding
   Suggested skill: dev-feature-scaffold

Tips​

  • Run after at least 2 weeks of active development for meaningful patterns
  • Combine with /skill-create for end-to-end discovery-to-creation pipeline
  • Re-run monthly to detect new patterns as workflow evolves
  • Use --min-frequency=5 for high-activity repos to reduce noise

Learning​

This skill reads from:

jaan-to/learn/jaan-to-pm-skill-discover.learn.md

Add feedback:

/learn-add pm-skill-discover "Check for monorepo context mixing"