memory-management

You can translate workplace acronyms and shorthand into clear instructions for Claude by running a memory bootstrap to build a glossary and AGENTS.md. This enables Claude to decode internal language like project codes and nicknames into actionable tasks automatically.

Yes, you can use Obsidian vault context to decode internal language for an AI assistant. The system accesses the Obsidian vault via MCP to perform deeper context lookups, converting shorthand and internal language into concrete references.

The best way to maintain a glossary for decoding project codes and meeting notes is using a tiered memory system. It leverages a lightweight hot cache in AGENTS.md alongside a full knowledge base in glossary.md for scalable understanding.

Yes, this shorthand decoding approach works with company-specific context files. It performs tiered lookups across AGENTS.md, glossary.md, and a dedicated company context file to resolve internal language into clear actions.

Claude misunderstands internal team shorthand and project codes because it lacks your specific workplace vocabulary. By building a memory system with a glossary and context files, Claude can decode these acronyms into concrete references.

You need an MCP connection only if you want to access an Obsidian vault for deeper context. Basic acronym decoding works using the local tiered memory files, while MCP enables scalable lookups across external vault data.