Add skillmem to Knowledge & Memory

README.md

@@ -2955,6 +2955,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
 - [vishalbanwari26/mnemos](https://github.com/vishalbanwari26/mnemos) [![vishalbanwari26/mnemos MCP server](https://glama.ai/mcp/servers/vishalbanwari26/mnemos/badges/score.svg)](https://glama.ai/mcp/servers/vishalbanwari26/mnemos) 🐍 🏠 - Persistent memory with three swappable storage backends (Postgres/pgvector, Qdrant, Neo4j) behind one interface, benchmarked head-to-head for latency, not just claimed interchangeable. Retrieval weighting adapts per user via epsilon-greedy over real outcome feedback instead of a fixed formula. Reflection merges near-duplicate facts and decays/archives stale ones, audit-logged, never hard-deleted. Real before/after MCP eval: +60% answer accuracy with memory vs. without. `git clone` + `uv sync` (not yet on PyPI).
 - [pjpoulose/PIL](https://github.com/pjpoulose/PIL) [![pjpoulose/PIL MCP server](https://glama.ai/mcp/servers/pjpoulose/PIL/badges/score.svg)](https://glama.ai/mcp/servers/pjpoulose/PIL) 📇 🏠 🐍 🍎 🪟 🐧 - Personal Instagram Library: turns your Instagram saved posts into a private, AI-searchable knowledge base on your own machine. Vision-AI deep reads (summaries, key points, how-tos, links, tags) go into local SQLite, queried live through a read-only stdio MCP server by Cursor, Claude Code, and Claude Desktop — or as a static export for any AI tool. Code is shared, data stays home.
 - [Mnemosyne-OS/Mnemosyne-Neural-OS](https://github.com/Mnemosyne-OS/Mnemosyne-Neural-OS) [![Mnemosyne-OS/Mnemosyne-Neural-OS MCP server](https://glama.ai/mcp/servers/Mnemosyne-OS/Mnemosyne-Neural-OS/badges/score.svg)](https://glama.ai/mcp/servers/Mnemosyne-OS/Mnemosyne-Neural-OS) 🎖️ 📇 🏠 🍎 🪟 🐧 - Memory the human governs: vaults separated by domain (code, notes, journal) on your own machine, hybrid retrieval (BM25 fused with vectors by RRF), and a declared vault list, so a vault left out cannot be read by mistake. Also reads what the OTHER coding agents on this machine wrote to disk, and flags when two are live in the same git worktree. Needs the Mnemosyne OS desktop app running. `npx -y @mnemosyne_os/mcp`
+- [liza-studio/skillmem](https://github.com/liza-studio/skillmem) [![liza-studio/skillmem MCP server](https://glama.ai/mcp/servers/liza-studio/skillmem/badges/score.svg)](https://glama.ai/mcp/servers/liza-studio/skillmem) 🐍 🏠 🍎 🪟 🐧 - Self-improving skill memory for coding agents: skills that help get reinforced, unused ones fade on an Ebbinghaus decay curve. $0 write path (SQLite FTS5 + local ONNX embeddings, no LLM calls), bilingual EN/RU hybrid search, SHA256 tamper-evident history, deterministic LongMemEval benchmark in-repo (hit@5 0.871). 8 mem_* tools; deep Claude Code hook integration optional. `pip install skillmem`
 
 ### ⚖️ <a name="legal"></a>Legal
 Access to legal information, legislation, and legal databases. Enables AI models to search and analyze legal documents and regulatory information.