What problem does it solve? Autonomous agents lose context between sessions, repeating investigations and forgetting prior decisions. This Skill standardizes how the Gemini CLI Bot synchronizes with previous sessions, tracks task status, and preserves root-cause findings across runs. ## Core Features & Use Cases - Structured Memory File: Maintains lessons-learned.md with a Task Ledger, Hypothesis Ledger, Decision Log, and investigation findings sections. - Session Synchronization Rituals: Enforces a mandatory Phase 0 context retrieval (reading memory and verifying state via the GitHub CLI) and a Phase 6 memory preservation step at the end of each run. - Memory Pruning: Keeps only the 50 most recent tasks and 20 most recent decision entries to prevent context bloat. - Use Case: A scheduled bot run picks up where the last session ended by reading the Task Ledger, marks merged PRs as DONE, investigates failures, and appends new findings to the Decision Log before finishing. ## Quick Start Activate the memory skill to read lessons-learned.md, synchronize the task ledger with current GitHub state, and record your findings before finishing.