Memory Audit — Self-Cleaning Memory Lint

Trigger

• Auto-triggered during weekly review
• "Audit my memories", "clean up memory", "check for contradictions"
• When compiled summaries surface contradictions or gaps

What This Does

Runs a health check on Athena's long-term memory. Finds contradictions, stale facts, duplicates, orphans, and gaps. Fixes what it can, flags what it can't. This is the self-maintenance routine that keeps memory clean over months and years of use.

The 5 Checks

1. Contradictions

Search MemPalace for memories in the same room that conflict.

How: For each room, pull recent drawers and look for opposing claims (e.g., "loves running" vs "hates running", "works at Google" vs "works at Anthropic" with overlapping dates).

Resolution:

• Check timestamps. The newer one is probably more current.
• Check source tags. user_statement beats system_inference.
• If still ambiguous, flag for user confirmation: "I have conflicting info about [topic]. Which is current?"
• Use kg_invalidate to expire the outdated triple.

2. Stale Facts

Find KG triples and drawers that are old and unaccessed.

How: Query mempalace_kg_timeline for triples older than 6 months. Check if the drawer was accessed recently. Cross-reference with compiled summaries — is this fact still in the current summary?

Resolution:

• Don't auto-delete. Flag as "stale, may need update."
• During the next relevant conversation, gently verify: "Last I remember, you were [stale fact]. Still true?"

3. Duplicates

Find memories that say the same thing in different words.

How: MemPalace's duplicate detection (0.9 similarity threshold) catches exact matches. This check catches semantic duplicates below that threshold — memories that mean the same thing but are worded differently.

Resolution:

• Keep the one with the user_statement source tag.
• If both are user_statement, keep the more recent one.
• Delete the duplicate with mempalace_delete_drawer.

4. Orphans

Find drawers with no KG connections and low access count.

How: List all drawers, check which ones have no related KG entities. Sort by access count.

Resolution:

• If the orphan contains a meaningful fact, create KG connections for it.
• If it's low-value episodic noise, consider deletion.
• Don't delete aggressively — some orphans are valid standalone memories.

5. Gaps

Find important life domains with few or no memories.

How: Check each default room (career, health, relationships, goals, finances, identity). Count drawers per room. Flag rooms with fewer than 5 drawers as "sparse."

Resolution:

• Don't interrogate the user. Instead, surface gaps naturally during coaching: "I don't know much about your health habits. Want to share anything?"
• Add gap topics to the coaching queue for natural follow-up.

Output Format

After running, report:

Memory Audit — [date]
- Contradictions found: [N] (resolved: [N], flagged for user: [N])
- Stale facts flagged: [N]
- Duplicates removed: [N]
- Orphans reviewed: [N] (connected: [N], removed: [N])
- Sparse domains: [list]
- Memory health: [HEALTHY / NEEDS ATTENTION / CRITICAL]

Rules

• Never delete user_statement memories without user confirmation.
• Never delete more than 10 memories in a single audit without asking.
• Log every deletion and the reason.
• Run silently during weekly review — only surface issues if they need user input.