Decompose monolithic architecture.md into modular docs/architecture/ documents

The 751-line architecture.md violated the SDD process modular documentation
target (~500 lines). It also had duplicate TaskGraph class definitions (one
monolith, one decomposed) that directly contradicted each other, and embedded
consumer-specific tool dispatch mappings that belong in downstream projects.

Changes:
- Split into 8 focused documents + 7 ADR records + redirect page
- Removed the monolithic TaskGraph class (kept only decomposed version)
- Moved CLI→plugin dispatch mapping out (belongs in plugin architecture)
- Extracted implementation code (frontmatter splitter, findCycles, DAG
  propagation) into WHAT/WHY descriptions per architect role spec
- Added proper ADR format for all resolved design decisions
- Fixed review issues: C_fail mapping, DuplicateNodeError/DuplicateEdgeError
  types, ValidationError/GraphValidationError definitions, mutation error
  handling contract, enum naming convention, validation timing clarification

docs/architecture/decisions/002-rebuild-vs-incremental.md

@@ -0,0 +1,26 @@
+# ADR-002: Rebuild graph on change, not incremental updates
+
+**Status**: Accepted
+
+## Context
+
+When task data changes (file edits, DB updates), the in-memory graph needs to reflect the new state. Two approaches: incremental updates (add/remove individual nodes/edges) or full rebuild from source data.
+
+## Decision
+
+**Rebuild.** For our graph sizes (10–200 nodes), `graph.import()` from a serialized blob is sub-millisecond. Both consumers (alkhub builds from DB query results; OpenCode plugin rebuilds from directory on file change) are well-served by rebuild.
+
+## Consequences
+
+### Positive
+- No change-detection layer needed — no tracking ID renames, dependency removals, edge reconciliation
+- Simpler codebase — no diff algorithm, no incremental update logic
+- Always consistent — rebuild guarantees the graph matches the source data exactly
+
+### Negative
+- Technically wasteful for small changes (rebuilding entire graph when one task changed)
+- Not suitable for very large graphs or extremely frequent updates
+
+### Mitigation
+
+If a future use case requires incremental updates, add it as an optimization then. The API surface (construction methods) supports both patterns — incremental construction exists via `addTask`/`addDependency`.