docs(35-02): complete plan with SUMMARY and STATE update

- Add comprehensive SUMMARY.md with implementation details
- Update STATE.md: Phase 35, Plan 1/3 complete
- Track performance: 10 min, 378 lines of code
- Document key decisions and next phase readiness

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

.planning/phases/35-large-workflow-handling/35-02-SUMMARY.md

@@ -0,0 +1,102 @@
+---
+phase: 35-large-workflow-handling
+plan: 02
+subsystem: chat-context
+tags: [tdd, selection, subgraph, context-scoping]
+requires:
+  - src/types/nodes.ts (WorkflowNode type)
+  - src/types/workflow.ts (WorkflowEdge type)
+provides:
+  - src/lib/chat/subgraphExtractor.ts (extractSubgraph function)
+  - SubgraphResult interface for selection-aware context
+affects:
+  - Future chat context builder integration (plan 35-03)
+tech-stack:
+  - TypeScript
+  - Vitest (testing)
+key-files:
+  - src/lib/chat/subgraphExtractor.ts (89 lines)
+  - src/lib/chat/subgraphExtractor.test.ts (289 lines)
+key-decisions:
+  - Use Set for O(1) node lookup during edge classification
+  - Boundary connections track both direction and handle type
+  - Empty selection returns all nodes/edges with isScoped=false
+  - Type breakdown uses node.type directly (not node data)
+  - Handle type from sourceHandle/targetHandle with fallback to "unknown"
+duration: 10 minutes
+completed: 2026-01-31
+---
+
+# Selection-aware subgraph extraction for focused LLM context
+
+## Performance
+
+**Velocity:** 10 minutes (plan 35-02)
+**Code output:** 378 lines (89 implementation + 289 tests)
+**Test coverage:** 8 comprehensive test cases, all passing
+**Efficiency:** Clean TDD flow (RED -> GREEN, no refactor needed)
+
+## Accomplishments
+
+Implemented `extractSubgraph()` function that splits a workflow into detailed selected nodes and a lightweight summary of the rest. This enables context-aware chat where users can select specific nodes to focus the LLM's attention, crucial for large workflows with 50+ nodes.
+
+Key features:
+- O(1) node lookup using Set for efficient edge classification
+- Three-way edge classification: fully within selection, boundary, outside
+- Boundary connections identify direction (incoming/outgoing) and handle type
+- Type breakdown counts unselected nodes by type for LLM context
+- Empty selection returns full workflow (no scoping)
+
+## Task Commits
+
+| Phase | Commit | Description |
+|-------|--------|-------------|
+| RED | d102922 | test(35-02): add failing tests for subgraph extraction |
+| GREEN | e44bdfa | feat(35-02): implement extractSubgraph for selection-aware context |
+
+## Files Created/Modified
+
+**Created:**
+- `src/lib/chat/subgraphExtractor.ts` - Core extraction function with SubgraphResult interface
+- `src/lib/chat/subgraphExtractor.test.ts` - Comprehensive test suite (8 test cases)
+
+**Modified:**
+- None (net new functionality)
+
+## Decisions Made
+
+1. **Set-based lookup** - Use `new Set(selectedNodeIds)` for O(1) membership testing during edge classification (scales well for large workflows)
+
+2. **Boundary direction semantics** - "incoming" when target is selected (data flows INTO selection), "outgoing" when source is selected (data flows OUT of selection)
+
+3. **Handle type tracking** - Store sourceHandle/targetHandle on boundary connections so LLM knows what type of data is crossing the boundary (image vs text)
+
+4. **Empty selection behavior** - When `selectedNodeIds` is empty, return all nodes/edges with `isScoped=false` (no scoping applied)
+
+5. **Type breakdown source** - Use `node.type` directly rather than inspecting node data (simpler, faster)
+
+## Deviations from Plan
+
+None. Implementation followed plan exactly:
+- SubgraphResult interface as specified
+- All required test cases implemented
+- Edge classification logic matches spec
+- Boundary connection structure with direction/handleType fields
+
+## Issues Encountered
+
+None. Clean TDD execution with no blockers.
+
+## Next Phase Readiness
+
+**Ready for plan 35-03 (Chat Context Builder Integration):**
+- extractSubgraph function exported and tested
+- SubgraphResult interface provides all needed data
+- Boundary connections enable LLM to understand data flow across selection
+- Type breakdown gives high-level overview of unselected nodes
+
+**Integration points for 35-03:**
+- Call extractSubgraph() when user has selected nodes
+- Pass selectedNodes to detailed context builder
+- Format restSummary into concise text summary for LLM
+- Include boundary connections in context (e.g., "Node B receives image from Node A outside selection")