Store and retrieve user preferences, facts, notes, and rules across conversations.
npx skills add https://github.com/alsk1992/CloddsBot --skill memory-alsk1992
Please help me install this Agent Skill. Skill: memory Source: https://github.com/alsk1992/CloddsBot/tree/main/src/skills/bundled/memory Command: npx skills add https://github.com/alsk1992/CloddsBot --skill memory-alsk1992
This Skill provides a persistent memory system, allowing you to store, recall, and search preferences, facts, notes, and rules across conversations, ensuring no information is lost.
Use the memory skill to remember that your favorite cryptocurrency is Bitcoin.
High-intent search queries and answers about installing and using this skill.
You can store user preferences and facts across AI conversations by using a persistent memory system that saves data via backends like LanceDB, SQLite, or PostgreSQL. This ensures no user information is lost between sessions.
Semantic search finds saved notes by using vector embeddings to match information based on meaning rather than exact keywords. This allows the memory system to retrieve relevant context and facts even if the search terms differ from the stored text.
Yes, this persistent memory system works with PostgreSQL, SQLite, and LanceDB as its backends. This allows you to choose the database that best fits your existing infrastructure for storing user preferences and notes.
You can keep a daily journal of trades and activities by logging entries into the memory system, which records daily events and PnL for performance tracking. This stored context is then used to personalize AI interactions.
The best way to recall a specific rule without exact keywords is using semantic search through vector embeddings. This mechanism matches the meaning of your query to the stored rules, ensuring accurate retrieval.
shreed27Store, recall, and search persistent user data with a TypeScript API.
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thecloudtipsManage a persistent SQLite memory store with HNSW vector indexing.
