Where Was I ou total-recall

Persistent memory for Claude Code — at ~350 tokens ambient cost, with no Docker, no API keys, and no MCP servers. Engram captures your sessions structurally on PreCompact (zero LLM cost), extracts atomic memories via a single lightweight LLM digest (preferences, practices, current context), and detects emergent patterns from your history — files you always edit together, recurring errors, tool usage anomalies — stored as an auditable Obsidian-compatible wiki. Key features: • Per-project handoff notes — at session start you get a narrative message from the last session in this project • Atomic UPSERT memories keyed by topic — latest wins, no drift, no embeddings • Emergent pattern detection (co-edits, error recurrence, project streaks, tool anomalies) • Durable preferences stay global; ephemeral context is scoped per project • 4-flag CLI surface: --stats, --query, --memories, --forget • Everything local: SQLite at ~/.claude/memory.db, markdown wiki at ~/.claude/patterns/

Coding Agents forget everything when a session ends. total-recall fixes that: a shared memory layer that persists across sessions, tools, and devices. Memory is organized into three tiers (Hot / Warm / Cold) with a 4,000-token budget enforced automatically — so Claude gets relevant context injected at session start without carrying stale noise. Semantic search (all-MiniLM-L6-v2 embeddings, offline) retrieves the right memories on demand. A knowledge base lets you ingest READMEs, API docs, and architecture notes that are retrieved semantically when relevant. An eval framework lets you measure retrieval quality, run benchmarks, and compare config changes — so you know memory is actually helping. All state is local: SQLite + ONNX embeddings, no external services, no API keys required. Works across Claude Code, Copilot CLI, Cursor, Cline, and OpenCode — existing memories auto-import on first run.