Mining Hidden Skills from Claude Code Session Logs with Semantic Knowledge Graphs

The Problem If you use Claude Code (or any LLM-based coding agent) daily, you've probably noticed yourself repeating similar workflows. The natural next step is: Can we turn these into reusable Skills? The conventional path is: document your knowledge → codify it into a Skill → deploy. But in practice, the first step — articulating tacit knowledge as formal documentation — is where most people get stuck. You know what you do, but writing it down precisely enough for an agent to replicate is surprisingly hard. Here's the key insight: your session logs already contain that knowledge. Every time you correct the agent, choose a specific tool sequence, or guide a workflow, you're implicitly recording your decision-making process. The question is how to extract it. crune is the tool I built to answer that question. It analyzes Claude Code JSONL session logs, builds a semantic knowledge graph across sessions, detects recurring workflow patterns, and surfaces Skill candidates — all without req