Stores and recalls workflow patterns via the @lanonasis/mem-intel-sdk.
npx skills add https://github.com/thefixer3x/onasis-gateway --skill behavior-memory
Please help me install this Agent Skill. Skill: behavior-memory Source: https://github.com/thefixer3x/onasis-gateway/tree/main/.claude/skills/behavior-memory Command: npx skills add https://github.com/thefixer3x/onasis-gateway --skill behavior-memory
This Skill automates the capture and recall of successful workflow patterns, enabling AI agents to learn from past actions and improve future performance.
Use the behavior-memory skill to store the current workflow as a pattern.
High-intent search queries and answers about installing and using this skill.
You can capture and recall workflow patterns for an AI agent by using a memory intelligence SDK to store successful actions and retrieve them later. This enables behavioral pattern learning through cached embeddings and local-first processing.
Behavioral pattern learning is the process of recording successful workflows so AI agents can learn from past actions. It enables contextual recall of relevant past patterns to inform current actions and improve future performance.
The @lanonasis/mem-intel-sdk facilitates memory management by authenticating memory intelligence flows and utilizing local-first processing with cached embeddings. It provides an API fallback to efficiently store and search behavior patterns.
Yes, AI agents can recall past bug fixing steps using memory intelligence. By capturing the previously successful sequence of steps for similar authentication issues, the agent retrieves that pattern for faster resolution.
Local-first memory processing with cached embeddings does not strictly require an internet connection for core recall tasks. The system utilizes local cached embeddings and relies on an API fallback only when needed.
thefixer3xExtends the @lanonasis/mem-intel-sdk with TypeScript behavior recording, recall, and suggestion methods.
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kaifashraffManage private on-device memory for AI agents with LanceDB and JavaScript embeddings.
