effectiveness
Measures how often suggested coding patterns are reused to identify genuinely useful guidance versus noise for tuning pattern stores.
Instructions
Measure how often suggested patterns actually got used afterwards.
For each pattern returned by suggest() in the window, checks whether
it was observed again later. A high confirmation rate means the
pattern is genuinely useful guidance; a low rate means it is noise
that should be pruned.
Use this to tune your store — patterns below a threshold may belong
in alias_pattern() merges or gc() decay.
Args:
days: Look-back window in days. Default 30. Shorter windows
surface recent drift; longer windows measure long-term value.
Returns:
Dict with keys: "window_days" (int), "patterns" (list of
{pattern, suggested_count, confirmed_count, rate}), "overall_rate"
(float 0.0-1.0 across all patterns).
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| days | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||