- Fix HP007/HP013: add 'drawdown', 'biggest holding', 'top holdings' to
performance keyword lists so these queries route to portfolio_analysis
- Fix MS005: use word-boundary regex for short city tokens (sf, atx, dfw)
to prevent 'sf' substring-matching inside ticker symbols like 'MSFT',
which was incorrectly routing to real_estate_snapshot
- Fix MS010: route full_report_kws to performance+compliance+activity
(was 'compliance' only, missing transaction_query for 'recent activity')
- Fix sc-004: add common 'portfolio' typos (portflio, porfolio, etc.) to
natural_performance_kws for robustness against misspellings
- Fix MS005 (part 2): add 'worth today', 'worth now', 'currently worth'
to market_kws so cost-basis-vs-current-price queries trigger both
portfolio_analysis and market_data
All eval suites now pass: 182/182 pytest, 60/60 run_evals, 25/25 golden sets
Made-with: Cursor
Follow-up questions like 'how does this compare to inflation?',
'is that good?', 'what does this mean?' were NOT being detected
as context_followup because the old check only had 8 hardcoded
phrases (e.g. 'how does that compare' but not 'how does this compare').
This caused every follow-up to fall through to 'performance',
call portfolio_analysis again, and return the same portfolio
summary regardless of what the user actually asked.
Added a broader _broad_followup_phrases list (35 patterns) covering:
- 'how does this/that/it compare'
- 'what does this/that mean'
- 'is that good/bad/normal/high/low'
- 'compared to inflation/the market'
- 'why is that', 'break that down', etc.
Confirmed with runtime logs: old_phrase_matched=false for the
follow-up, broad_phrase_matched=true, tools_used=[] (correct).
Made-with: Cursor
- Created agent/evals/conftest.py: autouse fixture patches teleport_api._fetch_from_teleport
and search_city_slug to bypass all live HTTP calls during tests
- Tests now use HARDCODED_FALLBACK data for all cities (deterministic, instant)
- Created agent/pytest.ini with asyncio_mode=strict and testpaths=evals
- All 126 tests collected and passing: 0 failures, 0 skips
Made-with: Cursor
Remove 'total net worth' and 'everything i own' from wealth_net_worth_kws
so they fall through to property_net_worth_kws which runs property tracker
and shows the complete financial picture template.
Add 'show my total net worth' and related phrases to property_net_worth_kws.
Made-with: Cursor
Build pre-formatted financial picture template in property_net_worth executor.
Shows investment portfolio, real estate equity per property, total net worth,
and portfolio breakdown percentages. If no properties, prompts user to add one.
Template is passed as tool result so LLM presents it cleanly.
Made-with: Cursor
When user says 'add my home' without property details, return a warm
structured prompt asking for address, purchase price, current value,
mortgage balance, and monthly rent instead of calling add_property
with empty/zero values.
Detection: message lacks a price pattern (\$[\d,]+, \d+k, \d{5,}).
If message already contains a price, proceed directly to add_property.
Made-with: Cursor
Add _extract_strategy_params() helper to graph.py that parses
appreciation rate, buy interval, total years, home price, rent yield,
and annual income from natural language messages.
Update life_decision branch to detect strategy queries and route them
to simulate_real_estate_strategy() with extracted params instead of
calling the general life_decision_advisor. Supports conservative /
moderate / optimistic presets. Falls back to life_decision_advisor
for non-strategy queries.
Made-with: Cursor
Create realestate_strategy.py with simulate_real_estate_strategy().
All rate parameters (appreciation, rent_yield, mortgage_rate,
market_return) default to None — sensible fallbacks applied inside
the function body, clearly labeled as starting points not predictions.
Adds disclaimer, how_to_adjust, and user_provided flag in assumptions.
Adds test_realestate_strategy.py with 7 passing tests.
Made-with: Cursor
- Expand classify_node keyword lists for relocation_runway, wealth_gap,
equity_unlock, and family_planner to cover more natural phrasings
- Add realestate_strategy_kws block that routes multi-property strategy
queries ("buy a house every N years", "rental portfolio strategy") to
the life_decision executor (home_purchase decision type)
- Expand real_estate_kws with MLS/market-data terms and add "show me"
to _location_intent_kws so city + intent triggers correctly
- Update _route_after_classify with explicit routing map comment showing
all 9 non-write categories → "tools" (only existing node names used)
- Add tool categories block to SYSTEM_PROMPT so LLM knows to use
non-portfolio tool results instead of defaulting to portfolio framing
Made-with: Cursor
property_tracker.py:
- Full SQLite backing at agent/data/properties.db (PROPERTIES_DB_PATH for tests)
- :memory: support: module-level _MEMORY_CONN so data persists across calls in tests
- add_property(), get_properties(), list_properties() (alias), update_property(),
remove_property() (soft-delete), get_real_estate_equity(), get_total_net_worth()
- _row_to_dict() computes equity/appreciation and backward-compat added_at alias
- property_store_clear() does DELETE FROM (test reset)
test_wealth_bridge.py (8 new tests, total now 89):
- test_down_payment_austin_portfolio_94k: $94k covers Caldwell/Hays counties
- test_down_payment_small_portfolio: $20k cannot afford safe 20% down anywhere
- test_job_offer_seattle_not_real_raise: $180k Seattle < $120k Austin purchasing power
- test_job_offer_sf_genuine_raise: $250k SF > $80k Austin purchasing power
- test_job_offer_global_city_london: required fields present for any global city
- test_property_crud_full_cycle: CREATE→READ→UPDATE→DELETE all verified
- test_net_worth_combines_portfolio_and_property: equity + portfolio = correct total
- test_teleport_fallback_works_when_api_unavailable: always returns usable data
Made-with: Cursor
- New agent/tools/wealth_bridge.py with 3 registered agent tools:
* calculate_down_payment_power(): maps portfolio value to 7 Austin markets
(or any cities) with can_afford_full/conservative/safe + monthly payment estimates
* calculate_job_offer_affordability(): COL-adjusted salary comparison for any
two cities worldwide using ACTRIS COL index (Austin) + Teleport API (global)
* get_portfolio_real_estate_summary(): reads live Ghostfolio portfolio + runs
down payment analysis in one call
- graph.py: add wealth_bridge imports + 4 new query_type routes:
wealth_down_payment, wealth_job_offer, wealth_global_city, wealth_portfolio_summary
- graph.py: add _extract_salary, _extract_offer_city, _extract_current_city helpers
- Mortgage formula: 30yr @ 6.95%, 20% down, ×1.25 for PITI
Made-with: Cursor
- New agent/tools/teleport_api.py with search_city_slug() and get_city_housing_data()
- Live calls to api.teleport.org /scores/ and /details/ endpoints (no auth required)
- In-memory slug cache with 60+ pre-seeded city→slug mappings
- Normalizes Teleport data to unified schema (ListPrice, MedianRentMonthly,
AffordabilityScore, col_index, teleport_scores) compatible with ACTRIS structure
- HARDCODED_FALLBACK for 23 major cities when API is unreachable — never crashes
- Austin TX area detection routes callers back to real_estate.py (ACTRIS data)
- col_index derived from Teleport COL score for wealth_bridge calculations
Made-with: Cursor
- Use real data_source label from _MOCK_SNAPSHOTS (ACTRIS/Unlock MLS) in response envelope
- Append 📊 ACTRIS/Unlock MLS footer to all Texas market_summary responses
- Expose months_of_inventory, pending_sales_yoy, close_to_list_ratio, median_rent_monthly
- Fix compare_neighborhoods data_source attribution for mixed TX/non-TX comparisons
- All 7 counties already had real Jan 2026 MLS figures; this surfaces them properly
Made-with: Cursor
- ngOnInit restores conversation from sessionStorage on mount
- saveHistory() persists every message exchange automatically
- clearHistory() resets to welcome message and wipes stored history
- Clear button added to panel header (small, subtle, matches dark theme)
- welcomeMessage getter adapts copy based on enableRealEstate flag
Made-with: Cursor
- test_search_listings_bedroom_filter: min_beds=3 returns only 3+ bed
listings and records the filter in result.filters_applied.
- test_search_listings_price_filter: max_price=400000 excludes listings
above threshold and records filter in result.filters_applied.
- test_structured_error_code: all error paths return nested
{code, message} dict with a REAL_ESTATE_* code.
- Updated test_feature_flag_disabled: assert nested error dict with
REAL_ESTATE_FEATURE_DISABLED code.
- Updated test_unknown_location_graceful_error: assert nested error
dict with REAL_ESTATE_PROVIDER_UNAVAILABLE code.
All 8 tests pass in < 1s.
Made-with: Cursor
Priyanka Punukollu