Explore how to leverage locally deployed Skills to empower your terminal AI (e.g., Cursor / Claude Code / Cline), turning scattered information into a structured personal knowledge engine.
Stop manually organizing scattered notes and PDFs. Feed materials to your local Agent, and it will automatically format, extract core conclusions, and accurately place them into the local Markdown directory tree.
User: "Read the paper PDF I just dragged in, extract the core conclusions, organize it into notes and save it to my /tech-fundamentals folder."Isolated notes lack value. The Agent will scan your local knowledge base to discover connections between new notes and existing projects or interview experiences, automatically building bidirectional links.
User: "Scan my local knowledge base, find connections between this new note and my previous RecSys projects, and automatically add bidirectional links."Based on the Ebbinghaus forgetting curve, the Agent extracts weak points from your knowledge base to generate exclusive flashcards or daily study plans, continuously solidifying your foundation.
User: "Based on my knowledge base records, my grasp of the RAG architecture is weak recently. Please give me 3 short-answer questions to review and update my study plan."Say goodbye to generic and empty AI outputs. When generating resumes or mock interviews, the Agent first deeply reads your highly correlated local work experiences to perform hallucination-free reasoning.
User: "I want to apply for a Senior MLE position at Google. Please extract the 3 most highly relevant STAR project experiences based on my local project repo, and help me polish my resume."Post-combat experience is invaluable. Send the transcript of a mock or real interview to the Agent, and it will analyze your blind spots, automatically triggering the next learning cycle.
User: "Here is the transcript of my recent Mock Interview. Please help me analyze my blind spots and update my capability model and study plan."