Workflow Analyzer

Parameters

• days (optional): Number of days to analyze, defaults to 30
  • Examples: "analyze my workflows from the last 7 days", "analyze my workflows from the last 60 days"

Analysis Criteria

The skill considers a pattern significant if it:

• Appears 3+ times in the analyzed period
• Has consistent structure across occurrences
• Represents meaningful time investment
• Could be automated as a single slash command

Patterns Detected

The skill identifies these common workflow patterns:

1. Git workflows: add/commit/push sequences, branch operations, PR creation
2. Version/publish sequences: version bumps, plugin/marketplace updates, releases
3. Documentation updates: README changes, consistency checks, sync operations
4. Implementation cycles: plan → build → test patterns, phase-based development
5. Test/fix cycles: test execution, error fixing, validation loops

Usage Instructions

When the user requests workflow analysis:

1. Calculate date range:

   • Use the days parameter if provided, otherwise default to 30
   • Calculate cutoff timestamp: date -v-{days}d +%s (macOS) or date -d "{days} days ago" +%s (Linux)

2. Locate session files:

   find ~/.claude/projects -name "*.jsonl" -type f -mtime -{days} 2>/dev/null
   

3. Run analysis and generate report:

   find ~/.claude/projects -name "*.jsonl" -type f -mtime -{days} 2>/dev/null | \
     python3 <skill-path>/scripts/workflow_analyzer.py
   

4. Present findings:

   • Display the complete markdown report to the user
   • Highlight top 3 automation opportunities
   • Include specific time savings estimates
   • Provide concrete next steps

Report Deliverables

The generated report includes:

Analysis Summary

• Time period analyzed (date range)
• Number of sessions reviewed
• Number of user prompts examined
• Total patterns detected

High-Priority Patterns (ranked by impact)

For each pattern:

• Pattern name and description
• Frequency of occurrence
• Example user request sequences (actual prompts from sessions)
• Suggested command name (verb-noun format)
• Estimated time per occurrence and total time spent
• Potential time savings with automation

Project-Specific Insights

• Which projects show the most repeated workflows
• Project-specific automation opportunities
• Activity distribution across projects

Recommendations

• Which commands to create first (ranked by ROI)
• Estimated time savings for top suggestions
• Implementation complexity assessment
• Next steps for the user

Privacy

• All analysis is performed locally only
• No data is sent to external services
• Session transcripts never leave the user's machine
• All processing happens in-memory with no temporary files created

Success Criteria

This skill is successful if it:

• Accurately identifies patterns the user actually repeats
• Provides specific, actionable automation suggestions
• Shows clear time savings estimates
• Presents findings in a scannable, useful format
• Completes in reasonable time (< 2 minutes for 30 days of data)

Example Invocations

• "Analyze my workflows"
• "What workflows am I repeating in Claude Code?"
• "Analyze my workflows from the last 60 days"
• "Find automation opportunities in my Claude Code usage"
• "Show me what I'm doing repeatedly"

Notes

• The skill focuses on user prompts, not system messages or command outputs
• Patterns must appear 3+ times to be considered significant
• Time estimates are based on typical workflow execution times
• Suggested command names follow verb-noun convention (e.g., /ship-git, /publish-plugin)