What problem does it solve? AI coding sessions in Cursor accumulate as raw SQLite and JSONL transcripts full of unverified claims. This Skill distills those transcripts into structured packets, verifies each claim against the actual codebase with toolchain evidence, and promotes only confirmed facts into a canonical session knowledge base. ## Core Features & Use Cases - Batch Deep Distillation: Processes 3 Cursor sessions per batch via deep-distill-run.py, generating lossless packets and answer-packets with extracted claims. - Verification-Gated Promotion: Every claim must be verified with Grep/Read/git/Shell evidence and marked ANSWERED before promotion to the canonical knowledge base; contradicted or stale claims are flagged. - Storage Cleanup: Purges archived sessions from Cursor's state.vscdb, conversation-search.db, workspace storage, and agent-transcripts with automatic backups. - Use Case: After weeks of Cursor Composer sessions on a project, run a deep distill batch to extract reusable lessons, verify them against the current repo HEAD, and append only proven facts to session-knowledge-base.md. ## Quick Start Ask the AI to run the Cursor deep distill workflow on the next batch of three sessions and promote only toolchain-verified answers to the session knowledge base.