alias_pattern
Merge duplicate patterns in AI memory by redirecting observations from one pattern to another, consolidating confidence without data loss.
Instructions
Redirect all future observations of one pattern onto another.
Use this to merge duplicates: when the same concept has been recorded
under two keys (e.g. "seq:a->b" and "seq:a -> b" with a space), alias
the stray into the canonical one. Existing confidence is summed into
the target so no learning is lost.
The target must already exist. Use find_duplicates() to discover
merge candidates, then call this to apply them.
Args:
pattern: The key to retire. Future observations of this key will
be rerouted silently.
target: The canonical key to absorb into. Must already exist in
the store.
Returns:
On success: {"aliased": <pattern>, "target": <target>}.
On failure (target missing): {"error": "target pattern '<target>'
not found"} — check for the "error" key.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | Yes | ||
| target | Yes |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||