gh-princespaghetti-claude-marketplace-learnfrompast/skills/workflow-analyzer/SKILL.md

name, description, invocation

name	description	invocation
workflow-analyzer	Analyzes Claude Code session history to identify repeated workflows and suggest slash commands to automate them	Ask Claude to "analyze my workflows" or "find repeated patterns in my Claude Code usage"

Workflow Analyzer Skill

Purpose

This skill analyzes your Claude Code usage patterns by examining session transcripts to identify workflows you repeat frequently. It suggests specific slash commands you could create to automate these patterns, complete with time savings estimates and implementation priorities.

When to Use

Use this skill when you want to:

• Identify repeated workflows in your Claude Code sessions
• Discover automation opportunities
• Get specific recommendations for slash commands to create
• Understand your development patterns and time investment
• Optimize your Claude Code workflow efficiency

How It Works

This skill includes a pre-built Python analysis script that:

1. Parses session JSONL files from ~/.claude/projects/*/
2. Identifies repeated patterns in user requests across sessions
3. Detects common workflows (git operations, documentation updates, testing cycles, etc.)
4. Generates a comprehensive report with automation recommendations

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)