memlens Tracks Down Memory Retrieval Failures
Feisty_Dog_1198 · reddit · 2026-07-15
The author built a tool called memlens specifically designed to track down why an AI agent's memory retrieval "failed to recall."
The Problem Solved
- Existing memory tools usually only return the final relevant results.
- But during actual debugging, the more critical questions are:
- Was it never stored in the first place?
- Was the score too low?
- Was it silently filtered out by a threshold?
How memlens Works
- It doesn't handle retrieval itself; instead, it wraps a trace layer that logs the complete scoring and retention reasons for every candidate memory.
- It currently supports two adapters:
- mnemos: Natively exposes the true score of each candidate.
- mem0: Bypasses the public API's hidden thresholds to fetch all candidates first, then reapplies thresholds based on the actual logic to reveal the filtered-out candidates.
- It also provides a terminal viewer, memlens view trace.json, for easy trace inspection.
The author explicitly positions it as a debugging layer to "observe the true scoring process," rather than just another retriever that fabricates scores.
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