Analyzes recent conversation history using chat tools to identify recurring workflow patterns and generate Custom Skills recommendations with statistical rigor. Use when users request workflow analysis, pattern identification, skill generation suggestions, or automation opportunities based on their AI usage patterns without requiring conversation exports.
View on GitHubhirefrank/hirefrank-marketplace
claude-skills-analyzer
plugins/claude-skills-analyzer/skills/workflow-pattern-analyzer/SKILL.md
January 16, 2026
Select agents to install to:
npx add-skill https://github.com/hirefrank/hirefrank-marketplace/blob/main/plugins/claude-skills-analyzer/skills/workflow-pattern-analyzer/SKILL.md -a claude-code --skill workflow-pattern-analyzerInstallation paths:
.claude/skills/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](../../shared/analysis-methodology.md)** 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](../../shared/analysis-methodology.md)** 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 com