coder-memory-recall

Semantic search retrieves relevant coding patterns and lessons from a wiki knowledge base to inform complex debugging or architecture decisions. It uses qmd for semantic and keyword search with a scoped brain2 wiki, falling back to grep if needed.

Use memory recall for non-trivial software engineering tasks including debugging ambiguous bugs, architecture decisions, performance tuning, or unfamiliar domains. Skip recall for trivial lookups because querying the wiki knowledge base is computationally expensive.

Memory recall primarily uses qmd for semantic and keyword search to locate coding knowledge within a brain2 wiki scope, falling back to grep if the primary search method is unavailable or insufficient for retrieving the necessary lessons.

Yes, you can query a brain2 wiki to pull domain-specific coding patterns, bugs, and design decisions. This targeted recall informs architecture decisions by retrieving universal coding lessons from a dedicated code-knowledge repository.

The main limitation is cost; recalling coding knowledge is computationally expensive and should be skipped for trivial tasks. It is designed strictly for complex debugging or architectural studies, meaning simple lookups waste resources and should be avoided.