Retrieve Past Decisions

20.2. Retrieve Past Decisions — Bringing Back Decisions Already Made

Cross-session search via FTS5

Unlike memory (which only holds a few condensed facts), retrieving the full context of an old decision/conversation uses full-text search (SQLite FTS5) plus LLM summarization when needed — allowing a past decision to be recalled in detail without the user having to retell it from the beginning.

"Which approach did I decide to use for X before?"
→ the agent calls session_search on its own to look it back up, instead of asking you again

The operating principle is clear: when the user mentions something from a previous conversation, or when the agent suspects relevant context exists from another session, it should use session_search to remember before asking the user to repeat themselves.

The difference from Memory — complementary, not a replacement

Memory (20.1) is a condensed summary, always present in every prompt. Session search is the full archive, queried only when needed — the two layers complement each other: Memory tells you “something happened”, session search tells you “exactly how it happened”.

Notes

• When you need the agent to recall a specific technical decision discussed long ago (not just a short fact), ask in a way that cues the context — the agent will look it up on its own instead of guessing or starting over from scratch.
• For decisions that truly matter and must be remembered accurately for the long term, consider proactively turning them into a condensed Memory entry (20.1) instead of relying only on session search — to avoid the case where old session content gets archived or is hard to retrieve exactly.