docs: mark Task 1.3 complete (migration already handled by schema)

Task 1.3 (Create Migration Script) is satisfied by existing code:
- python -m data_processing.migrate creates all pathway tables
- pathway_date_filters auto-populated via INSERT OR REPLACE in schema
- Verified: fresh database creates all 3 tables with 6 date filters

IMPLEMENTATION_PLAN.md

@@ -59,9 +59,12 @@ cd pathways_app && timeout 60 python -m reflex run 2>&1 | head -30
 - [x] Verify: `python -c "from data_processing.pathway_pipeline import *"`
 
 ### 1.3 Create Migration Script
-- [ ] Create script to set up new tables in existing `data/pathways.db`
-- [ ] Pre-populate `pathway_date_filters` with 6 combinations
-- [ ] Verify migration runs cleanly on fresh database
+- [x] Create script to set up new tables in existing `data/pathways.db`
+  - Note: Existing `python -m data_processing.migrate` handles this (updated in Task 1.1)
+- [x] Pre-populate `pathway_date_filters` with 6 combinations
+  - Note: Auto-populated via INSERT OR REPLACE in PATHWAY_DATE_FILTERS_SCHEMA
+- [x] Verify migration runs cleanly on fresh database
+  - Verified: All 3 pathway tables created, 6 date filters populated correctly
 
 ## Phase 2: CLI Refresh Command
 

progress.txt

@@ -121,3 +121,37 @@ The `ids` column in ice_df contains hierarchical paths like:
 - The refresh command needs: DATE_FILTER_CONFIGS, compute_date_ranges(), and pipeline functions
 ### Blocked items:
 - None
+
+## Iteration 3 — 2026-02-04
+### Task: 1.3 Create Migration Script
+### Why this task:
+- Task 1.2 (Pipeline) was complete, and this was the next task in sequence
+- Following the logical order: Schema → Pipeline → Migration → CLI Command
+- Smaller, focused task before tackling the more complex CLI refresh command
+### Status: COMPLETE
+### What was done:
+- Discovered that Task 1.3 is already satisfied by work done in Task 1.1:
+  - `python -m data_processing.migrate` already creates all pathway tables via `create_all_tables()`
+  - `pathway_date_filters` is auto-populated via INSERT OR REPLACE in the schema
+  - All helper functions (`verify_pathway_tables_exist`, `get_pathway_table_counts`, etc.) already exist
+- Verified by running the migrate CLI against a fresh temp database:
+  - All 3 pathway tables created successfully
+  - All 6 date filter rows pre-populated correctly
+  - Status output shows pathway tables in table counts
+### Validation results:
+- Tier 1 (Code): ✅ python -m data_processing.migrate runs without errors
+- Tier 2 (Visual): N/A (CLI/schema work, no UI)
+- Tier 3 (Functional): ✅ Fresh database test shows all tables created with correct row counts
+### Files changed:
+- `IMPLEMENTATION_PLAN.md` — marked Task 1.3 subtasks complete with notes
+### Committed: f976324 "docs: mark Task 1.3 complete (migration already handled by schema)"
+### Patterns discovered:
+- Good architecture in Task 1.1 (including schema auto-population) made Task 1.3 trivial
+- The INSERT OR REPLACE pattern in schema is powerful — eliminates need for separate population scripts
+### Next iteration should:
+- Start Task 2.1: Create CLI Refresh Command (`cli/refresh_pathways.py`)
+- This is the first task with real new work to do
+- Reference `data_processing/pathway_pipeline.py` for DATE_FILTER_CONFIGS, compute_date_ranges()
+- The CLI needs to: parse args, fetch Snowflake data, process all 6 filters, insert to SQLite, log status
+### Blocked items:
+- None