vestige/CHANGELOG.md

Changelog

All notable changes to Vestige will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[1.1.2] - 2025-01-27

Fixed

• Embedding model cache now uses platform-appropriate directories instead of polluting project folders
  • macOS: ~/Library/Caches/com.vestige.core/fastembed
  • Linux: ~/.cache/vestige/fastembed
  • Windows: %LOCALAPPDATA%\vestige\cache\fastembed
• Can still override with FASTEMBED_CACHE_PATH environment variable

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[1.1.1] - 2025-01-27

Fixed

• UTF-8 string slicing issues in keyword search and prospective memory
• Silent error handling in MCP stdio protocol
• Feature flag forwarding between crates
• All GitHub issues resolved (#1, #3, #4)

Added

• Pre-built binaries for Linux, Windows, and macOS (Intel & ARM)
• GitHub Actions CI/CD for automated releases

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[1.1.0] - 2025-01-26

Changed

• Tool Consolidation: 29 tools → 8 cognitive primitives
  • recall, semantic_search, hybrid_search → search
  • get_knowledge, delete_knowledge, get_memory_state → memory
  • remember_pattern, remember_decision, get_codebase_context → codebase
  • 5 intention tools → intention
• Stats and maintenance moved from MCP to CLI (vestige stats, vestige health, etc.)

Added

• CLI admin commands: vestige stats, vestige health, vestige consolidate, vestige restore
• Feedback tools: promote_memory, demote_memory
• 30+ FAQ entries with verified neuroscience claims
• Storage modes documentation: Global, per-project, multi-Claude household
• CLAUDE.md templates for proactive memory use
• Version pinning via git tags

Deprecated

• Old tool names (still work with warnings, removed in v2.0)

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[1.0.0] - 2025-01-25

Added

• FSRS-6 spaced repetition algorithm with 21 parameters
• Bjork & Bjork dual-strength memory model (storage + retrieval strength)
• Local semantic embeddings with fastembed v5 (BGE-base-en-v1.5, 768 dimensions)
• HNSW vector search with USearch (20x faster than FAISS)
• Hybrid search combining BM25 keyword + semantic + RRF fusion
• Two-stage retrieval with reranking (+15-20% precision)
• MCP server for Claude Desktop integration
• Tauri desktop application
• Codebase memory module for AI code understanding
• Neuroscience-inspired memory mechanisms:
  • Synaptic Tagging and Capture (retroactive importance)
  • Context-Dependent Memory (Tulving encoding specificity)
  • Spreading Activation Networks
  • Memory States (Active/Dormant/Silent/Unavailable)
  • Multi-channel Importance Signals (Novelty/Arousal/Reward/Attention)
  • Hippocampal Indexing (Teyler & Rudy 2007)
• Prospective memory (intentions and reminders)
• Sleep consolidation with 5-stage processing
• Memory compression for long-term storage
• Cross-project learning for universal patterns

Changed

• Upgraded embedding model from all-MiniLM-L6-v2 (384d) to BGE-base-en-v1.5 (768d)
• Upgraded fastembed from v4 to v5

Fixed

• SQL injection protection in FTS5 queries
• Infinite loop prevention in file watcher
• SIGSEGV crash in vector index (reserve before add)
• Memory safety with Mutex wrapper for embedding model

[0.1.0] - 2026-01-24

Added

• Initial release
• Core memory storage with SQLite + FTS5
• Basic FSRS scheduling
• MCP protocol support
• Desktop app skeleton