Analyzes action logs to identify recurring workflows and suggest new automation opportunities.
Pattern Miner is a diagnostic tool designed to optimize development workflows by mining execution data from historical action logs. By parsing activity files, it uncovers repetitive tasks, hidden dependencies, and consistent manual patterns that are ripe for automation. Instead of guessing where efficiency can be improved, this skill provides data-driven proposals for new automations and skill implementations, helping developers transition from manual execution to streamlined, AI-assisted routines within their local workstation.
Key Features
01Generates a structured PATTERNS.md file to document optimization findings.
02Analyzes ACTION_LOG files to detect high-frequency task sequences.
03Adheres to safety guardrails by proposing rather than auto-executing changes.
040 GitHub stars
05Identifies complex dependencies between recurring development actions.
06Proposes specific Claude Code skill ideas based on observed user behavior.
Use Cases
01Auditing quantitative research workflows to discover common backtesting or visualization patterns.
02Transforming a sequence of manual data cleaning steps into a reusable automation script.
03Identifying redundant Git or deployment commands to streamline project maintenance.
