Search persistent memory stores using keyword and semantic queries.
npx skills add https://github.com/popoffvg/dotfiles --skill context-find
Please help me install this Agent Skill. Skill: context-find Source: https://github.com/popoffvg/dotfiles/tree/main/harness/plugins/memory-keeper/claude/skills/context-find Command: npx skills add https://github.com/popoffvg/dotfiles --skill context-find
Retrieve relevant insights from persistent memory to answer user questions with context-aware information. Always check memory before responding to topic-based questions to avoid repeating or fabricating information.
Ask me to search your memory with /context find <query> to retrieve relevant insights.
High-intent search queries and answers about installing and using this skill.
To retrieve insights from persistent memory, you can search memory stores using both keyword and semantic search to locate relevant notes and context, ensuring responses are informed by previously stored information rather than fabricated.
Searching project notes across memory stores is best handled by leveraging semantic search with fallbacks, which locates insights using concept-based matching to quickly summarize what is known about a topic.
Memory recall requires reading the insights root configuration from a specific local markdown file path to successfully retrieve and apply persistent memory context to project overviews.
Extracting a project overview by searching memory with exact keywords is fully supported, utilizing keyword search to quickly summarize known information across various memory items and notes.
When standard keyword search fails to find relevant notes in memory, the system applies deep search and z-core fallback mechanisms to retrieve full content and ensure context-aware information is located.
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Percona-LabStore and retrieve persistent memory using Notion pages.
