check-memory

To stop redundant file reads, you can enforce a memory-first workflow that forces the system to query recalled knowledge before performing any code search or file exploration. This grounds responses in existing memory and skips unnecessary disk operations.

A memory-first workflow requires querying stored knowledge—such as past decisions, architecture, and conventions—before answering questions or exploring code. This prevents redundant work by surfacing recalled facts prior to initiating any new file reads or searches.

You can check project memory by invoking specific recall shortcuts like memory.decisions, memory.architecture, and memory.conventions. These queries surface relevant historical facts and stored knowledge before you proceed with active code browsing or project analysis.

Yes, you can safely explore code on disk through a safe fallback workflow. This approach transparently combines the incomplete recalled knowledge with on-disk file exploration, providing clear source citations for every piece of information surfaced.

You can keep sensitive data out of project memory by utilizing privacy-safe contexts. These contexts ensure that sensitive information remains excluded from memory storage unless explicitly allowed, maintaining security during project analysis and knowledge recall.

Your AI assistant repeats unnecessary code searches because it lacks a enforced memory-check step before responding. Forcing the system to consult memory shortcuts for decisions and architecture before file reads eliminates this redundant exploration.