P10: Indexing Agent History
What You Do
Search over past agent session logs two ways: scan every event file, then build a database/index. Measure the data returned, latency, token counts, and real cost of each, and see where the scan stops fitting in the model's context window at all.
Harness Mechanism
A naive substring scan over the raw event log vs. a SQLite FTS5 index over extracted event text, returning ranked top-K. Real token counts and billed cost come from the Anthropic API.
Open First
Keep
A one-line policy on when agent history needs an index.
The main lesson: unbounded history that the agent queries every run has no upper bound when scanned and routinely exceeds the context window. Index extracted text, not raw events, and return ranked top-K.