Workflow Pattern Analyzer

Workflow Pattern Analyzer

Instructions

This skill provides comprehensive conversation pattern analysis using Claude's native chat history tools (recent_chats and conversation_search) to identify skill-worthy automation opportunities with the statistical rigor of export-based analysis.

Core Capabilities:

• Web interface compatible (no exports required)
• Statistical pattern validation and scoring
• Frequency analysis and temporal tracking
• Evidence-based skill recommendations
• Complete skill package generation

Analysis Framework

This skill uses the shared analysis methodology with tool-based data collection adaptations.

Phase 1: Data Collection Strategy

Determine Analysis Scope:

Ask user: "How deep should I analyze your conversation history?"

Options:

• Quick Scan (20-30 conversations, ~2-3 min): Recent patterns and immediate opportunities
• Standard Analysis (50-75 conversations, ~5-7 min): Comprehensive pattern detection
• Deep Dive (100+ conversations, ~10-15 min): Full workflow mapping with temporal trends
• Targeted Search (variable): Focus on specific topics or time periods

Data Collection Process:

1. Broad Sampling: Use recent_chats(n=30) multiple times with varied parameters to get diverse coverage
2. Temporal Distribution: Sample conversations across different time periods (recent, 1 week ago, 1 month ago)
3. Topic Exploration: Use conversation_search for domains mentioned by user or detected in initial sampling
4. Depth vs Breadth: Balance comprehensive coverage with processing efficiency

Phase 2-6: Core Analysis

Apply the shared analysis methodology phases:

• Phase 2: Pattern Discovery & Classification (explicit, implicit, domain, temporal)
• Phase 3: Frequency Analysis & Validation (occurrence metrics, statistical validation)
• Phase 4: Skill-Worthiness Scoring (0-50 composite scale across 5 dimensions)
• Phase 5: Relationship Mapping & Consolidation (overlap detection, boundary optimization)
• Phase 6: Prioritization Matrix & Recommendations (frequency vs impact visualization)

See shared methodology for complete scoring rubrics and quality standards.

Phase 7: Skill Package Generation

For each approved skill, create:

A. Skill Specification Document:

## [Skill Name]

**Pattern Evidence:**
- Frequency: [X instances in Y conversations (Z%)]
- Consistency: [X/10 score]
- Time savings: [X hours/month]

**Composite Score: [X/50]**
- Frequency: [X/10]
- Consistency: [X/10]
- Complexity: [X/10]
- Time Savings: [X/10]
- Error Reduction: [X/10]

**Example Conversations:**
1. [Date]: [Brief excerpt showing pattern]
2. [Date]: [Brief excerpt showing pattern]
3. [Date]: [Brief excerpt showing pattern]

**Pattern Components:**
- **Consistent elements**: [What stays the same]
- **Variable elements**: [What changes per instance]
- **Common refinements**: [Typical adjustments user makes]

**Proposed Skill Structure:**

SKILL.md sections:
1. Overview & trigger conditions
2. [Main workflow methodology]
3. Quality standards
4. Examples

Supporting files needed:
- reference.md: [Detailed framework/methodology]
- templates/: [Reusable output templates]
- examples.md: [Additional use cases]

B. Complete SKILL.md File:

Generate production-ready skill with:

• Proper YAML frontmatter (name, description with triggers)
• Clear instructions based on pattern analysis
• Evidence-based examples from actual conversations
• Quality standards derived from user refinement patterns
• Progressive disclosure (link to references for detail)

Output Formats

After analysis completion, present:

Summary Report

# Workflow Pattern Analysis Report
**Analysis Date**: [Timestamp]
**Conversations Analyzed**: [X conversations across Y time period]
**Patterns Identified**: [X patterns]
**Skills Recommended**: [Y skills]

## 🔥 HIGH-PRIORITY OPPORTUNITIES

### 1. [Skill Name]
**Score: [X/50]** (Frequency: X/10, Consistency: X/10, Complexity: X/10, Time: X/10, Error: X/10)

**Pattern Description**: [What you do repeatedly]

**Evidence**:
- Found in [X] conversations ([Y%] of analyzed sample)
- First seen: [Date], Most recent: [Date]
- Average time per instance: [X minutes]

**Example Occurrences**:
1. [Date]: "[Brief excerpt]"
2. [Date]: "[Brief excerpt]"

**Proposed Skill**: "[One-line skill description]"

**Time Savings**: [X hours/month]

---

[Repeat for top 5-8 patterns]

## 💡 MODERATE OPPORTUNITIES
[Briefer summaries of medium-priority patterns]

## 🎯 QUICK AUTOMATION CANDIDATES
[Simple, high-frequency patterns]

## ⏸️  DEFERRED PATTERNS
[Patterns that didn't meet skill-worthiness thresholds]

## 📊 ANALYSIS METADATA
- Total conversations: [X]
- Date range: [earliest] to [latest]
- Unique patterns identified: [X]
- Patterns validated: [Y]
- Cross-pattern overlaps: [Z]
- Recommended consolidations: [N]

Interactive Follow-Up Options

What would you like to do next?

A. Generate complete SKILL.md files for [top 3-5 skills]
B. Deep dive into specific pattern: [skill name]
C. Expand analysis with more conversations
D. Focus on specific domain/topic area
E. Adjust scoring weights and recalculate priorities

Quality Standards

All quality standards follow the shared analysis methodology:

• Pattern validation requirements (frequency, consistency, evidence)
• Skill consolidation rules (max 8-12 skills, clear boundaries)
• Skill package generation standards
• Anti-patterns to avoid

Progressive Disclosure Strategy

Keep this SKILL.md concise by referencing:

• Core methodology: shared/analysis-methodology.md
• Detailed scoring rubrics: See methodology Phase 4
• Quality standards: See methodology Quality Standards section
• Anti-patterns: See methodology Anti-Patterns section

Load additional context only when:

• User requests deep dive on specific pattern
• Generating complete skill packages (not just analysis)
• User wants to understand scoring methodology in detail
• Building reference materials for complex domains

Examples

Example 1: Quick Scan Request

User: "Analyze my recent chats for automation opportunities"

Claude: I'll perform a quick scan of your recent conversation history to identify skill opportunities.

[Uses recent_chats(n=30) multiple times]

📊 Quick Scan Results (30 conversations analyzed)

🔥 TOP OPPORTUNITY:

"Email Response Composer" - Score: 42/50

• Found in 9 conversations (30%)
• Pattern: You regularly ask me to draft professional emails with specific tone and structure requirements
• Time savings: ~90 min/month (10 min per email × 9 emails)
• Evidence: Consistent 3-paragraph structure with greeting, main content, action items

Want me to: A. Generate complete skill package for this B. Continue analysis for more patterns (expand to 50-75 conversations) C. Focus on other domains

Example 2: Targeted Domain Analysis

User: "Find patterns in how I use you for coding tasks"

Claude: I'll analyze your coding-related conversations to identify workflow patterns.

[Uses conversation_search for coding terms + recent_chats filtering]

📊 Coding Workflow Analysis (18 relevant conversations)

🔥 TOP PATTERNS:

1. "Code Review Checklist Generator" - Score: 38/50

   • Found in 7 code review discussions
   • Pattern: You ask for language-specific review checklists before reviewing PRs
   • Consistency: 85% (always includes security, performance, style sections)

2. "API Documentation Humanizer" - Score: 35/50

   • Found in 5 documentation tasks
   • Pattern: Converting technical API specs into developer-friendly guides
   • Structure: Always includes quick start, common use cases, troubleshooting

Want me to build skills for these patterns?

Example 3: Deep Dive Analysis

User: "Do a comprehensive analysis of my workflow over the last few months"

Claude: I'll perform a deep analysis of your conversation history. This will take 10-15 minutes to ensure comprehensive coverage.

[Uses recent_chats extensively, conversation_search for discovered topics, temporal sampling]

📊 Comprehensive Workflow Analysis

• Conversations analyzed: 120
• Date range: [3 months]
• Patterns identified: 15
• Skills recommended: 6

🔥 CRITICAL PRIORITY (Score 40-50):

1. "Weekly Status Report Generator" - Score: 47/50
   • Frequency: 12 instances (10% of conversations)
   • Consistency: 95% - always same structure
   • Evidence: Every Monday, you format updates in identical 5-section template
   • Time savings: 240 min/month (20 min/week × 4 weeks × 3 months avg)

⭐ HIGH PRIORITY (Score 30-39):

2. "Client Proposal Framework" - Score: 36/50
3. "Meeting Notes Structurer" - Score: 34/50
4. "Technical Concept Explainer" - Score: 31/50

[Full analysis report with evidence, prioritization matrix, skill specifications]

Recommended Implementation Path:

1. Start with "Weekly Status Report Generator" (highest ROI)
2. Build "Client Proposal Framework" and "Meeting Notes Structurer" next (complementary workflows)
3. Evaluate remaining patterns after 2-4 weeks of usage

Generate complete skill packages now? [Y/N]

When to Use This Skill

✅ Use this skill when:

• User requests analysis of their conversation patterns
• User wants to identify automation opportunities
• User asks what skills they should create
• User mentions repetitive tasks or workflows
• User wants evidence-based skill recommendations
• User is in web interface (can't use export-based analysis)

❌ Don't use this skill when:

• User has conversation export files available (use export-based plugin instead for more comprehensive analysis)
• User wants cross-platform ChatGPT + Claude analysis (requires exports)
• User has very few conversations (<10) making pattern detection unreliable
• User wants to build specific skill they already have in mind
• User is asking about existing skills or community skills

⚡ Proactive Use: When you detect potential patterns during normal conversation, offer:

💭 Pattern detected: This is the [Xth] time you've asked me to [action].

Would you like me to analyze your conversation history for similar 
patterns and recommend a Custom Skill? I can identify other automation 
opportunities you might not have noticed.

[Yes, analyze] [Not now]

Anti-Patterns to Avoid

See shared methodology anti-patterns for complete guidance on:

• Tasks not suitable for skills
• Red flags in patterns
• When to use MCP vs skills
• Common recommendation pitfalls

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