auto_term_empty_streak — the counter the 2026-08-06 review added to catch
exactly this — read 50 and climbing. Fifty consecutive curiosity scans where
the soul's dynamic seeding produced nothing and the loop fell back to four
hardcoded phrases. The live WM top said why in one look: every slot was a
Memory node labelled "memory:remembered". The extractor read the LABEL only,
the sentinel guard correctly rejects sentinels, so there was never anything
to extract. It was written against Knowledge nodes, which have real titles,
and was structurally blind to the node type that dominates working memory.
Rather than add a sixth guard to the five that accumulated across four
reviews (genre words, quoted titles, stopwords, label-df), invert the
algorithm. The old one was: take the first word, then check whether it is
acceptable. That shape forces quality to be expressed as rejection, and
rejection can only ever encode floods that already happened.
engram_salient_term() scores EVERY candidate token and returns the argmax of
idf · position · casing (YAKE, Campos et al. 2020, with real corpus IDF
substituted for YAKE's corpus-free proxies), falling back from a sentinel
label to the node's content. Term quality becomes the selection criterion
instead of a veto: a bad token loses to a better token in the same text
without needing to be on any list. Tabu is applied during the argmax, so
inhibition-of-return costs seed quality rather than costing the whole scan.
Two defects found by instrumenting rather than assuming, which is the lesson
this codebase keeps relearning:
- The first live run returned five ALL-CAPS terms in a row. Memory content
conventionally opens with an all-caps header, so YAKE's acronym bonus was
handing the seed to whatever word the heading started with. Restricted to
tokens <= 5 chars, where all-caps is evidence of an acronym rather than
evidence of a heading. Long headers now compete on specificity.
- df via istr_contains is substring matching, so "them" hit inside "theme"
and function words came back with nonzero df. Added word-boundary df
locally; engram_label_df keeps substring semantics for its callers.
An earlier draft claimed the min_df floor subsumed the 73 stopwords that
08-03 measured label-df as missing. Re-measured: about:2, whole:1, them:2 —
they clear a floor of 1. The claim was false and the comment now records the
correction. The floor buys lexical reachability; the argmax buys quality; the
stopword list still earns its keep.
Measured on 60 live Memory nodes before shipping: 0 empty, versus 60 of 60
under the old extractor. Terms are topical — HEBBIAN, CONSOLIDATION,
TEMPORAL, crash-loop, PRIMING, NEIGHBORHOOD, DRIFT. Three of sixty are weak
header words; left alone deliberately, because listing them is the move that
produced four blocklists.
ENGRAM_ST_DEBUG=1 dumps the scored candidate set. It exists because there was
no way to see whether the all-caps run was the corpus or the casing weight
without guessing.
will.anderson
ba6e36c3f7