Retrieve top-k scored memory chunks from @seed/memory for current tasks.
npx skills add https://github.com/phyter1/seed --skill recall-phyter1
Please help me install this Agent Skill. Skill: recall Source: https://github.com/phyter1/seed/tree/main/.claude/skills/recall Command: npx skills add https://github.com/phyter1/seed --skill recall-phyter1
This Skill enables users to access and retrieve the most relevant stored memories from @seed/memory, helping to provide contextual awareness for ongoing tasks or decisions.
Ask the AI to recall the last relevant decisions or events related to your current project.
High-intent search queries and answers about installing and using this skill.
To retrieve past context for decision-making, query the stored memory sources to fetch top-k scored memory chunks. This provides historical context and relevant past interactions to inform your current tasks.
Contextual memory retrieval is the process of scoring and fetching relevant historical memory chunks to provide context for ongoing tasks. You need it when preparing reports or making decisions that require recalling past incidents.
Yes, you can use retrieved memories to troubleshoot issues and ensure consistency. By recalling relevant past decisions or incidents, you maintain accuracy and align current actions with historical project context.
Scoring relevance works by evaluating and ranking stored memory chunks against your specific query. It operates within a scope of defined memory sources to ensure precise information retrieval for decision support.
A limitation of memory retrieval is that it operates strictly within defined memory sources, meaning it cannot access data outside its scoped boundaries. Relevance scoring is also limited to the chunks currently stored.
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