feat(infospace): add collection-level quality checks C1–C5 (S2.4)

Five concern checks: Redundancy (embedding/word overlap), Coverage
(FCA gap analysis), Coherence (graph connectivity), Consistency
(cycle detection), Granularity (Shannon entropy). Orchestrator runs
all or selected checks, CLI `markitect infospace check` command added.

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

markitect/infospace/checks/coherence.py

@@ -0,0 +1,81 @@
+"""
+C3 — Structural coherence.
+
+Uses graph analysis to check that the entity relationship graph is
+well-connected and has meaningful community structure.
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Dict, List, Optional
+
+from markitect.prompts.dependencies.models import DependencyGraph
+
+
+@dataclass
+class CoherenceReport:
+    """Results from coherence analysis."""
+
+    connected_components: int = 0
+    largest_component_size: int = 0
+    modularity: float = 0.0
+    community_count: int = 0
+    cohesion: float = 0.0
+    coupling: float = 0.0
+    entity_count: int = 0
+
+    def to_dict(self) -> dict:
+        return {
+            "concern": "C3",
+            "connected_components": self.connected_components,
+            "largest_component_size": self.largest_component_size,
+            "modularity": round(self.modularity, 4),
+            "community_count": self.community_count,
+            "cohesion": round(self.cohesion, 4),
+            "coupling": round(self.coupling, 4),
+            "entity_count": self.entity_count,
+        }
+
+
+def check_coherence(
+    graph: Optional[DependencyGraph] = None,
+    entity_count: int = 0,
+) -> CoherenceReport:
+    """Check structural coherence of the entity relationship graph.
+
+    Args:
+        graph: The entity relationship graph.  If ``None``, returns
+            a report with zero values.
+        entity_count: Total number of entities (for context).
+
+    Returns:
+        :class:`CoherenceReport` with connectivity and community metrics.
+    """
+    if graph is None or len(graph.nodes) == 0:
+        return CoherenceReport(entity_count=entity_count)
+
+    try:
+        from markitect.analysis.graph import (
+            connected_components,
+            modularity_score,
+            detect_communities,
+            cohesion_coupling,
+        )
+    except ImportError:
+        return CoherenceReport(entity_count=entity_count)
+
+    components = connected_components(graph)
+    communities = detect_communities(graph, seed=42)
+    mod = modularity_score(graph, communities=communities)
+    cc = cohesion_coupling(graph, communities=communities)
+
+    return CoherenceReport(
+        connected_components=len(components),
+        largest_component_size=len(components[0]) if components else 0,
+        modularity=mod,
+        community_count=len(communities),
+        cohesion=cc["cohesion"],
+        coupling=cc["coupling"],
+        entity_count=entity_count or len(graph.nodes),
+    )