What problem does it solve? Chat sessions with AI agents contain corrections, workarounds, and decisions that are lost unless someone reads every transcript and codifies them; this Skill processes session backlogs into durable, routed lessons so future sessions do not repeat the same mistakes. ## Core Features & Use Cases - Session queue and cursor management: Lists unprocessed transcripts per vendor via scripts/lesson-harvest.py and tracks processed state in censor/lesson-harvest.jsonl. - Lesson extraction and deduplication: Reads bounded session excerpts, identifies defects, corrections, and binding decisions, then checks precedents, levers, and memory files before writing anything new. - Routing cascade: Sends each new lesson to an existing terminus — a precedent entry, a his-hand lever, a memory file, or a board task through the conduct broker. - Use Case: When the lesson-harvest-backlog sensor reports unprocessed sessions, run a 10-session tranche to harvest lessons, mark each session processed, and report the remaining backlog count. ## Quick Start Ask the agent to process the newest ten unprocessed Claude chat sessions into lessons and report the remaining backlog.