feat(example): add per-entity LLM evaluations for 985 WoN entities (S3.3)

Batch evaluation of all 988 entities via OpenRouter. 984 succeeded on
first pass; 3 failed (network errors). eval-summary --update-metrics
written with per_entity_mean=3.9556.

Viability dashboard: 6/6 PASS
  redundancy_ratio   0.0061  (max 0.10)
  coverage_ratio     0.6190  (min 0.40)
  coherence_comps    0.0000  (max 3)
  consistency_cycles 0.0000  (max 0)
  granularity_entropy 2.6748 (min 1.0)
  per_entity_mean    3.9556  (min 3.5)

Dimension breakdown (mean across 985 entities):
  definition_precision  3.62
  source_grounding      4.36
  domain_placement      4.56
  vsm_relevance         3.31
  explanatory_value     3.94

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

examples/infospace-with-history/output/evaluations/economic_development_spatial_patterns.md

@@ -0,0 +1,63 @@
+---
+entity_slug: economic_development_spatial_patterns
+evaluator: null
+evaluated_at: '2026-02-23T05:10:21.656054'
+overall_score: 4.0
+scores:
+- name: definition_precision
+  value: 4.0
+  max_value: 5.0
+  rationale: The definition clearly identifies a distinct concept about geographical
+    arrangements of economic activity based on specific factors (market access, transportation
+    costs, division of labour). It avoids circularity and provides concrete examples
+    of clustering patterns.
+- name: source_grounding
+  value: 5.0
+  max_value: 5.0
+  rationale: This entity is directly grounded in Smith's analysis from Book I, Chapter
+    3, which explicitly discusses how industry clusters along coasts and navigable
+    rivers, how specialization relates to market size, and how isolation leads to
+    economic backwardness.
+- name: domain_placement
+  value: 4.0
+  max_value: 5.0
+  rationale: The entity fits well within economic geography and development theory
+    domains. While no specific domain is assigned, it clearly belongs in spatial economics
+    or economic geography rather than pure theory or policy domains.
+- name: vsm_relevance
+  value: 3.0
+  max_value: 5.0
+  rationale: This entity has moderate VSM relevance, primarily mapping to S4 (intelligence/environmental
+    adaptation) as it describes how economic systems adapt to geographical and infrastructural
+    environments. It could also relate to S1 (operations) in terms of where primary
+    economic activities locate.
+- name: explanatory_value
+  value: 4.0
+  max_value: 5.0
+  rationale: The entity provides genuine explanatory power by illuminating the structural
+    mechanisms behind economic clustering and development patterns. It explains why
+    certain locations become economically developed while others remain backward,
+    going beyond mere description to identify causal factors.
+---
+
+# Evaluation: Economic Development Spatial Patterns
+
+## definition_precision — 4.0 / 5.0
+
+The definition clearly identifies a distinct concept about geographical arrangements of economic activity based on specific factors (market access, transportation costs, division of labour). It avoids circularity and provides concrete examples of clustering patterns.
+
+## source_grounding — 5.0 / 5.0
+
+This entity is directly grounded in Smith's analysis from Book I, Chapter 3, which explicitly discusses how industry clusters along coasts and navigable rivers, how specialization relates to market size, and how isolation leads to economic backwardness.
+
+## domain_placement — 4.0 / 5.0
+
+The entity fits well within economic geography and development theory domains. While no specific domain is assigned, it clearly belongs in spatial economics or economic geography rather than pure theory or policy domains.
+
+## vsm_relevance — 3.0 / 5.0
+
+This entity has moderate VSM relevance, primarily mapping to S4 (intelligence/environmental adaptation) as it describes how economic systems adapt to geographical and infrastructural environments. It could also relate to S1 (operations) in terms of where primary economic activities locate.
+
+## explanatory_value — 4.0 / 5.0
+
+The entity provides genuine explanatory power by illuminating the structural mechanisms behind economic clustering and development patterns. It explains why certain locations become economically developed while others remain backward, going beyond mere description to identify causal factors.