Client Guides
Graph health
Keep your memory connected, de-duplicated and easy to recall
Recall is only as good as the graph behind it. A healthy graph has well-described nodes, few orphans, no duplicates and relationships that say why things are connected. Most of this happens automatically; this guide covers what you can do on top.
What HyperMemory does for you
| How | |
|---|---|
| Enrichment | After every write, background workers expand thin descriptions, extract data, detect people and organizations and link them. |
| Memory workers | The Enrichment worker discovers relationships and types, merges duplicates, cleans up orphans and detects hyperedges. Run it now or on a schedule from Memory Workers in the dashboard. |
| The memory-writer | The plugins’ writer agent stores each fact as its own node, links it to its siblings and cleans up after ingests. |
Find orphans
hm_list_orphans lists nodes that aren’t connected to the main graph:
hm orphans --limit 100
For each one, either connect it to its context with hm_add_relationships, or delete it with hm_forget if it’s junk. Orphans appear most often after hm_ingest.
Merge duplicates
When two nodes describe the same thing:
- Read both with
hm_get_nodes. - Rewrite the better one with
hm_updateso it holds everything that’s true. - Re-create the other’s relationships on it with
hm_add_relationships. - Delete the other with
hm_forget.
Fix vague relationships
A relationship that just says “related to” or “mentions” doesn’t help recall. Replace it with one that explains the connection — “Alice owns the Acme renewal”, “checkout uses Redis for sessions”. Edges’ wording can be changed with hm_update and the edge’s edge_id.
Audit memory quality
The memory-quality-audit system skill grades your graph on recall accuracy, description quality, relationships, categorization and coherence, and recommends fixes. Ask your agent:
Get the memory-quality-audit skill with hm_skill and run it on my graph.
Habits that keep a graph healthy
- Recall before you store. Update existing memories instead of creating near-duplicates.
- One node per fact, decision, preference or risk — not one big event that buries them.
- Lead descriptions with the point, and keep IDs and paths in
data. - Always store with at least one relationship.
- Correct, don’t append. When something changes, rewrite the description to say what’s true now.