Search notes, chat logs, and filesystem index with semantic matching.
npx skills add https://github.com/bishwashere/cowCode --skill memory-bishwashere
Please help me install this Agent Skill. Skill: Memory Source: https://github.com/bishwashere/cowCode/tree/main/skills/memory Command: npx skills add https://github.com/bishwashere/cowCode --skill memory-bishwashere
This skill enables fast retrieval of relevant information across your notes, chat history, and filesystem index by performing semantic search.
Search across MEMORY.md, memory/*.md, and chat logs for relevant past notes and conversations.
High-intent search queries and answers about installing and using this skill.
Semantic search across notes and chat logs surfaces relevant past context by querying MEMORY.md, memory/*.md files, and filesystem listings. It uses auto-indexing to keep results up to date without manual intervention.
Yes, semantic search supports filtering results by specific date ranges and content type, including notes, chat logs, and filesystem listings, allowing you to narrow down recalled context precisely.
Auto-indexing automatically processes notes and chat logs to keep search results current. It safely handles memory content during indexing to ensure new information is available for retrieval without manual updates.
Semantic search is the best way to locate information in a personal knowledge base, querying memory files and chat logs to surface relevant details based on meaning rather than exact keyword matches.
The system relies on memory_save, memory_get, and memory_search tools to store and retrieve information. It interacts directly with MEMORY.md and memory/*.md files to manage your knowledge base.
Search capabilities depend on safe handling of memory content during auto-indexing. While it supports notes, chat logs, and filesystem listings, precise filtering by date and type is required to manage large volumes effectively.
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