Developer Builds Local Markdown Vault to Carry Personal Context Across AI Tools

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A developer created SelfContext after growing frustrated with having to re-explain personal history, goals, and past decisions at the start of every new AI session. Existing solutions like provider memory, chat history, and note folders failed to reliably retain the context that actually mattered. SelfContext is a local layer of plain Markdown files paired with skills that instruct an existing AI agent to ingest, retrieve, and maintain that context over time. The vault runs entirely on disk with no proprietary server, database, or custom interface, making it portable across different AI tools and harnesses. The project distinguishes between what the user said, what sources stated, and what the model inferred, keeping all inferences reviewable so AI suggestions cannot silently overwrite personal goals or preferences.

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