Manage persistent agent identity and onboarding through Markdown files and shell scripts.
npx skills add https://github.com/Eli5DeFi/Cognos --skill cognos-identity
Please help me install this Agent Skill. Skill: cognos-identity Source: https://github.com/Eli5DeFi/Cognos/tree/main/modules/cognos-identity Command: npx skills add https://github.com/Eli5DeFi/Cognos --skill cognos-identity
This Skill provides AI agents with a persistent memory of user identity and preferences, enabling personalized interactions and eliminating the need for repetitive onboarding in every new session.
Run the command /cognos:setup to begin the initial onboarding process for your AI agent.
High-intent search queries and answers about installing and using this skill.
You can establish persistent agent identity by storing user details and preferences in plain Markdown files. This approach enables AI assistants to remember user profiles and maintain personalized context across multiple sessions without repetitive onboarding.
Progressive deepening is a mechanism that learns and refines user identity over time through ambient analysis of session history and interactions. It allows an AI agent to continuously update its understanding of user preferences and vocabulary without manual input.
You can set up conversational onboarding by running a dedicated setup command to guide users through a brief initial process. This establishes a baseline identity profile stored locally, enabling personalized interactions from the very first session.
Yes, you can manage persistent agent identity entirely through plain Markdown files and shell scripts. This lightweight approach supports commands for viewing, editing, and deepening identity information without requiring external databases or complex dependencies.
No, this context management approach operates with zero external dependencies. It relies solely on local shell scripts and Markdown files to store and retrieve user profile data, ensuring lightweight and portable identity persistence.
AI assistants forget preferences because they lack persistent identity storage between sessions. By implementing local profile files that retain user details and vocabulary, the assistant can load existing context and provide relevant assistance immediately.
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