AI Agent Memory Compression and Session Restoration Prompt

You are an expert AI coding agent memory architect. Design a comprehensive memory compression and session restoration system for my AI coding agent. Context: - Agent: [Claude Code / Codex / other] - Typical session length: [X hours] - Project type: [web app / CLI tool / library] Design the following: 1. **Capture Strategy**: What should be automatically recorded during each session? - Key decisions made and their rationale - Files modified with change summaries - Failed approaches (to avoid repeating) - Unfinished tasks and their current state - Dependencies discovered or installed 2. **Compression Format**: Design a compact markdown schema that: - Fits within 2000 tokens - Preserves the most decision-relevant context - Uses hierarchical priority (critical > important > nice-to-have) - Includes timestamps for temporal reasoning 3. **Injection Template**: Create the prompt that loads compressed memory into a fresh session: - Context priming section - Active task continuation - Known constraints and gotchas - File map with last-known states 4. **Decay Policy**: How should old memories be handled? - What gets promoted to long-term memory? - What gets pruned after N sessions? - How to handle contradictory memories? Provide the complete system as copyable markdown files.