diff --git a/apps/finance-ai-agent-demo/backend/agent/sprawl_tools.py b/apps/finance-ai-agent-demo/backend/agent/sprawl_tools.py
index faebcb77..6496a71e 100644
--- a/apps/finance-ai-agent-demo/backend/agent/sprawl_tools.py
+++ b/apps/finance-ai-agent-demo/backend/agent/sprawl_tools.py
@@ -581,3 +581,135 @@ def convergent_search_sprawl(
         return f"No results found for account '{account_id}'"
 
     return json.dumps(all_results, default=str)
+
+
+# ---------------------------------------------------------------------------
+# suggest_portfolio_hedge (PostgreSQL sprawl mode)
+# ---------------------------------------------------------------------------
+
+
+def suggest_portfolio_hedge_sprawl(pg_conn, args, query_logger):
+    """Hedge recommendation tool for sprawl/PostgreSQL mode.
+
+    Mirrors _suggest_portfolio_hedge in tools.py but uses PostgreSQL syntax
+    (%(param)s placeholders, JSONB operators, window functions).
+    """
+    import json as _json
+
+    account_id = args.get("account_id", "")
+    risk_focus = args.get("risk_focus", "all")
+
+    sql = """
+        WITH holdings AS (
+            SELECT
+                ph.holding_id,
+                ph.asset_class,
+                ph.instrument_name,
+                ph.ticker,
+                ph.sector,
+                ph.region,
+                ph.risk_rating,
+                ph.current_value,
+                SUM(ph.current_value) OVER () AS total_value,
+                ROUND(
+                    ph.current_value / NULLIF(SUM(ph.current_value) OVER (), 0) * 100, 2
+                ) AS pct_of_portfolio,
+                ca.risk_profile,
+                ca.metadata->>'esg_mandate' AS esg_mandate,
+                ca.metadata->>'max_single_position' AS max_position,
+                ca.metadata->'excluded_sectors' AS excluded_sectors
+            FROM portfolio_holdings ph
+            JOIN client_accounts ca ON ca.account_id = ph.account_id
+            WHERE ph.account_id = %(account_id)s
+        ),
+        sector_exposure AS (
+            SELECT sector,
+                   ROUND(SUM(pct_of_portfolio)::numeric, 2) AS sector_pct
+            FROM holdings
+            GROUP BY sector
+            ORDER BY sector_pct DESC
+        ),
+        region_exposure AS (
+            SELECT region,
+                   ROUND(SUM(pct_of_portfolio)::numeric, 2) AS region_pct
+            FROM holdings
+            GROUP BY region
+            ORDER BY region_pct DESC
+        ),
+        asset_class_exposure AS (
+            SELECT asset_class,
+                   ROUND(SUM(pct_of_portfolio)::numeric, 2) AS asset_class_pct
+            FROM holdings
+            GROUP BY asset_class
+            ORDER BY asset_class_pct DESC
+        ),
+        high_risk_positions AS (
+            SELECT holding_id, instrument_name, ticker, sector, region,
+                   risk_rating, pct_of_portfolio
+            FROM holdings
+            WHERE risk_rating >= 7
+            ORDER BY pct_of_portfolio DESC
+        )
+        SELECT 'HOLDING'        AS row_type,
+               h.holding_id     AS id,
+               h.instrument_name AS label,
+               h.ticker         AS ticker,
+               h.sector         AS sector,
+               h.region         AS region,
+               h.asset_class    AS asset_class,
+               h.risk_rating    AS risk_rating,
+               h.pct_of_portfolio AS pct,
+               h.risk_profile   AS risk_profile,
+               h.esg_mandate    AS esg_mandate,
+               h.max_position   AS max_position,
+               h.excluded_sectors::text AS excluded_sectors
+        FROM holdings h
+        UNION ALL
+        SELECT 'SECTOR', sector, sector, NULL, NULL, NULL, NULL,
+               NULL, sector_pct, NULL, NULL, NULL, NULL
+        FROM sector_exposure
+        UNION ALL
+        SELECT 'REGION', region, region, NULL, NULL, NULL, NULL,
+               NULL, region_pct, NULL, NULL, NULL, NULL
+        FROM region_exposure
+        UNION ALL
+        SELECT 'ASSET_CLASS', asset_class, asset_class, NULL, NULL, NULL, NULL,
+               NULL, asset_class_pct, NULL, NULL, NULL, NULL
+        FROM asset_class_exposure
+        UNION ALL
+        SELECT 'HIGH_RISK', holding_id, instrument_name, ticker, sector, region,
+               NULL, risk_rating, pct_of_portfolio, NULL, NULL, NULL, NULL
+        FROM high_risk_positions
+    """
+
+    columns = [
+        "ROW_TYPE",
+        "ID",
+        "LABEL",
+        "TICKER",
+        "SECTOR",
+        "REGION",
+        "ASSET_CLASS",
+        "RISK_RATING",
+        "PCT",
+        "RISK_PROFILE",
+        "ESG_MANDATE",
+        "MAX_POSITION",
+        "EXCLUDED_SECTORS",
+    ]
+
+    rows, _ = execute_query(
+        pg_conn,
+        sql,
+        {"account_id": account_id},
+        query_logger,
+        description=f"Hedge analysis (PostgreSQL): {account_id}",
+    )
+
+    if not rows:
+        return f"No holdings found for account '{account_id}'"
+
+    from agent.tools import _build_hedge_recommendations
+
+    results = [dict(zip(columns, row, strict=False)) for row in rows]
+    return _json.dumps(_build_hedge_recommendations(results, account_id, risk_focus), default=str)
diff --git a/apps/finance-ai-agent-demo/backend/agent/tools.py b/apps/finance-ai-agent-demo/backend/agent/tools.py
index 9fef65b6..d34eefb5 100644
--- a/apps/finance-ai-agent-demo/backend/agent/tools.py
+++ b/apps/finance-ai-agent-demo/backend/agent/tools.py
@@ -235,6 +235,39 @@
             },
         },
     },
+    {
+        "type": "function",
+        "function": {
+            "name": "suggest_portfolio_hedge",
+            "description": (
+                "Analyze a portfolio's risk factors — sector concentration, regional exposure, "
+                "asset class distribution, and individual position risk ratings — then recommend "
+                "specific hedging instruments (inverse ETFs, commodities, bonds, defensive equities, "
+                "options strategies) with clear reasoning tied to the actual holdings. "
+                "Use this when a client asks how to protect their portfolio, reduce risk, or hedge "
+                "against market downturns, sector-specific events, or geopolitical risks."
+            ),
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "account_id": {
+                        "type": "string",
+                        "description": "The account ID to analyze and generate hedge recommendations for",
+                    },
+                    "risk_focus": {
+                        "type": "string",
+                        "enum": ["market", "sector", "regional", "currency", "all"],
+                        "description": (
+                            "The type of risk to hedge against: 'market' for broad market downturns, "
+                            "'sector' for sector-specific concentration risk, 'regional' for geographic "
+                            "exposure, 'currency' for FX risk, 'all' for a comprehensive hedge plan"
+                        ),
+                    },
+                },
+                "required": ["account_id"],
+            },
+        },
+    },
 ]
 
 # Preloaded tools: always available to the LLM regardless of query or DB state.
@@ -302,6 +335,10 @@ def execute_tool(tool_name, tool_args):
                 return convergent_search_sprawl(
                     pg_conn, neo4j_driver, qdrant_client, embedding_model, tool_args, query_logger
                 )
+            elif tool_name == "suggest_portfolio_hedge":
+                from agent.sprawl_tools import suggest_portfolio_hedge_sprawl
+
+                return suggest_portfolio_hedge_sprawl(pg_conn, tool_args, query_logger)
             else:
                 return f"Error: Unknown tool '{tool_name}'"
         else:
@@ -324,6 +361,8 @@ def execute_tool(tool_name, tool_args):
                 return _find_nearby_clients(conn, tool_args, query_logger)
             elif tool_name == "convergent_search":
                 return _convergent_search(conn, embedding_model, tool_args, query_logger)
+            elif tool_name == "suggest_portfolio_hedge":
+                return _suggest_portfolio_hedge(conn, tool_args, query_logger)
             else:
                 return f"Error: Unknown tool '{tool_name}'"
 
@@ -634,6 +673,437 @@ def _find_nearby_clients(conn, args, query_logger):
     return json.dumps(results, default=str)
 
 
+def _suggest_portfolio_hedge(conn, args, query_logger):
+    """Analyze portfolio risk factors and recommend hedging instruments (Oracle mode).
+
+    Uses a single SQL statement (Relational + JSON + Analytics) to compute:
+    - Sector concentration and dominant sectors
+    - Regional exposure breakdown
+    - Asset class distribution
+    - High-risk positions (risk_rating >= 7)
+    - Account-level risk profile and ESG mandate from JSON metadata
+    """
+    account_id = args.get("account_id", "")
+    risk_focus = args.get("risk_focus", "all")
+
+    # Single query: Relational + JSON + window-function analytics
+    sql = """
+        WITH holdings AS (
+            SELECT
+                ph.holding_id,
+                ph.asset_class,
+                ph.instrument_name,
+                ph.ticker,
+                ph.sector,
+                ph.region,
+                ph.risk_rating,
+                ph.current_value,
+                SUM(ph.current_value) OVER () AS total_value,
+                ROUND(ph.current_value / NULLIF(SUM(ph.current_value) OVER (), 0) * 100, 2) AS pct_of_portfolio,
+                ca.risk_profile,
+                JSON_VALUE(ca.metadata, '$.investment_preferences.esg_mandate') AS esg_mandate,
+                JSON_VALUE(ca.metadata, '$.investment_preferences.max_single_position') AS max_position,
+                JSON_QUERY(ca.metadata, '$.investment_preferences.excluded_sectors') AS excluded_sectors
+            FROM portfolio_holdings ph
+            JOIN client_accounts ca ON ca.account_id = ph.account_id
+            WHERE ph.account_id = :account_id
+        ),
+        sector_exposure AS (
+            SELECT sector,
+                   ROUND(SUM(pct_of_portfolio), 2) AS sector_pct
+            FROM holdings
+            GROUP BY sector
+            ORDER BY sector_pct DESC
+        ),
+        region_exposure AS (
+            SELECT region,
+                   ROUND(SUM(pct_of_portfolio), 2) AS region_pct
+            FROM holdings
+            GROUP BY region
+            ORDER BY region_pct DESC
+        ),
+        asset_class_exposure AS (
+            SELECT asset_class,
+                   ROUND(SUM(pct_of_portfolio), 2) AS asset_class_pct
+            FROM holdings
+            GROUP BY asset_class
+            ORDER BY asset_class_pct DESC
+        ),
+        high_risk_positions AS (
+            SELECT holding_id, instrument_name, ticker, sector, region,
+                   risk_rating, pct_of_portfolio
+            FROM holdings
+            WHERE risk_rating >= 7
+            ORDER BY pct_of_portfolio DESC
+        )
+        SELECT
+            'HOLDING'        AS row_type,
+            h.holding_id     AS id,
+            h.instrument_name AS label,
+            h.ticker         AS ticker,
+            h.sector         AS sector,
+            h.region         AS region,
+            h.asset_class    AS asset_class,
+            h.risk_rating    AS risk_rating,
+            h.pct_of_portfolio AS pct,
+            h.risk_profile   AS risk_profile,
+            h.esg_mandate    AS esg_mandate,
+            h.max_position   AS max_position,
+            h.excluded_sectors AS excluded_sectors
+        FROM holdings h
+        UNION ALL
+        SELECT 'SECTOR', sector, sector, NULL, NULL, NULL, NULL,
+               NULL, sector_pct, NULL, NULL, NULL, NULL
+        FROM sector_exposure
+        UNION ALL
+        SELECT 'REGION', region, region, NULL, NULL, NULL, NULL,
+               NULL, region_pct, NULL, NULL, NULL, NULL
+        FROM region_exposure
+        UNION ALL
+        SELECT 'ASSET_CLASS', asset_class, asset_class, NULL, NULL, NULL, NULL,
+               NULL, asset_class_pct, NULL, NULL, NULL, NULL
+        FROM asset_class_exposure
+        UNION ALL
+        SELECT 'HIGH_RISK', holding_id, instrument_name, ticker, sector, region,
+               NULL, risk_rating, pct_of_portfolio, NULL, NULL, NULL, NULL
+        FROM high_risk_positions
+    """
+
+    columns = [
+        "ROW_TYPE",
+        "ID",
+        "LABEL",
+        "TICKER",
+        "SECTOR",
+        "REGION",
+        "ASSET_CLASS",
+        "RISK_RATING",
+        "PCT",
+        "RISK_PROFILE",
+        "ESG_MANDATE",
+        "MAX_POSITION",
+        "EXCLUDED_SECTORS",
+    ]
+
+    rows, _ = execute_query(
+        conn,
+        sql,
+        {"account_id": account_id},
+        query_logger,
+        description=f"Hedge analysis (Relational + JSON + Analytics): {account_id}",
+    )
+
+    if not rows:
+        return f"No holdings found for account '{account_id}'"
+
+    results = [dict(zip(columns, row, strict=False)) for row in rows]
+    return json.dumps(_build_hedge_recommendations(results, account_id, risk_focus), default=str)
+
+
+# ---------------------------------------------------------------------------
+# Hedge recommendation engine — pure Python, no DB calls
+# ---------------------------------------------------------------------------
+
+# Catalogue of hedge instruments keyed by risk dimension
+_HEDGE_CATALOGUE = {
+    "market": [
+        {
+            "ticker": "SH",
+            "name": "ProShares Short S&P500 ETF",
+            "type": "Inverse ETF",
+            "rationale": "Broad market hedge; gains when S&P 500 declines.",
+            "risk_level": "medium",
+        },
+        {
+            "ticker": "SQQQ",
+            "name": "ProShares UltraPro Short QQQ",
+            "type": "Leveraged Inverse ETF",
+            "rationale": "Aggressive tech/growth hedge (3× inverse NASDAQ-100). Suitable only for high-risk-tolerance accounts.",
+            "risk_level": "high",
+        },
+        {
+            "ticker": "GLD",
+            "name": "SPDR Gold Shares",
+            "type": "Commodity ETF",
+            "rationale": "Safe-haven asset; historically negatively correlated with equities during downturns.",
+            "risk_level": "low",
+        },
+        {
+            "ticker": "TLT",
+            "name": "iShares 20+ Year Treasury Bond ETF",
+            "type": "Bond ETF",
+            "rationale": "Long-duration Treasuries typically rise during risk-off equity sell-offs.",
+            "risk_level": "low",
+        },
+    ],
+    "sector": {
+        "Technology": [
+            {
+                "ticker": "REK",
+                "name": "ProShares Short Real Estate / rotate to Value",
+                "type": "Sector Rotation",
+                "rationale": "Rotate overweight tech into value/defensive sectors to reduce concentration.",
+                "risk_level": "low",
+            },
+            {
+                "ticker": "PUT",
+                "name": "Put options on QQQ",
+                "type": "Options Strategy",
+                "rationale": "Buy QQQ put options as targeted downside protection for tech-heavy portfolios.",
+                "risk_level": "medium",
+            },
+        ],
+        "Energy": [
+            {
+                "ticker": "ERY",
+                "name": "Direxion Daily Energy Bear 2× ETF",
+                "type": "Inverse ETF",
+                "rationale": "Inverse energy exposure; hedges oil/gas concentration risk.",
+                "risk_level": "high",
+            },
+            {
+                "ticker": "XLU",
+                "name": "Utilities Select Sector SPDR",
+                "type": "Defensive Equity ETF",
+                "rationale": "Utilities are low-beta defensives that offset cyclical energy holdings.",
+                "risk_level": "low",
+            },
+        ],
+        "Financials": [
+            {
+                "ticker": "SKF",
+                "name": "ProShares Ultra Short Financials",
+                "type": "Inverse ETF",
+                "rationale": "Inverse financials ETF; hedges bank and credit exposure.",
+                "risk_level": "high",
+            },
+        ],
+        "Healthcare": [
+            {
+                "ticker": "RXD",
+                "name": "ProShares Ultra Short Health Care",
+                "type": "Inverse ETF",
+                "rationale": "Hedges overweight healthcare/biotech concentration.",
+                "risk_level": "high",
+            },
+        ],
+        "DEFAULT": [
+            {
+                "ticker": "VXUS",
+                "name": "Vanguard Total International Stock ETF",
+                "type": "Diversification",
+                "rationale": "Broad international diversification reduces domestic sector concentration.",
+                "risk_level": "low",
+            },
+        ],
+    },
+    "regional": {
+        "North America": [
+            {
+                "ticker": "EFA",
+                "name": "iShares MSCI EAFE ETF",
+                "type": "Geographic Diversification",
+                "rationale": "Developed-market international exposure offsets US-heavy concentration.",
+                "risk_level": "low",
+            },
+        ],
+        "Europe": [
+            {
+                "ticker": "EPV",
+                "name": "ProShares Ultra Short FTSE Europe",
+                "type": "Inverse ETF",
+                "rationale": "Inverse European equities ETF; hedges European macro/political risk.",
+                "risk_level": "high",
+            },
+        ],
+        "Asia": [
+            {
+                "ticker": "EWJ",
+                "name": "iShares MSCI Japan ETF + short futures",
+                "type": "Hedged Exposure",
+                "rationale": "Currency-hedged Japan ETF reduces yen FX risk on Asian holdings.",
+                "risk_level": "medium",
+            },
+        ],
+        "DEFAULT": [
+            {
+                "ticker": "ACWX",
+                "name": "iShares MSCI ACWI ex US ETF",
+                "type": "Geographic Diversification",
+                "rationale": "Broad ex-US exposure balances home-country bias.",
+                "risk_level": "low",
+            },
+        ],
+    },
+    "currency": [
+        {
+            "ticker": "UUP",
+            "name": "Invesco DB US Dollar Index Bullish Fund",
+            "type": "Currency Hedge",
+            "rationale": "Long USD hedge against foreign-currency denominated international holdings.",
+            "risk_level": "medium",
+        },
+        {
+            "ticker": "FXE",
+            "name": "Invesco CurrencyShares Euro Trust",
+            "type": "Currency Hedge",
+            "rationale": "Direct EUR exposure hedge for portfolios with significant European assets.",
+            "risk_level": "medium",
+        },
+    ],
+}
+
+
+def _build_hedge_recommendations(rows, account_id, risk_focus):
+    """Derive risk factors from query rows and map to hedge recommendations."""
+    holdings = [r for r in rows if r["ROW_TYPE"] == "HOLDING"]
+    sectors = [r for r in rows if r["ROW_TYPE"] == "SECTOR"]
+    regions = [r for r in rows if r["ROW_TYPE"] == "REGION"]
+    asset_classes = [r for r in rows if r["ROW_TYPE"] == "ASSET_CLASS"]
+    high_risk = [r for r in rows if r["ROW_TYPE"] == "HIGH_RISK"]
+
+    # Pull account-level metadata from first holding row
+    meta = holdings[0] if holdings else {}
+    risk_profile = meta.get("RISK_PROFILE", "unknown")
+    esg_mandate = (meta.get("ESG_MANDATE") or "no").lower() == "yes"
+    excluded_sectors = []
+    try:
+        raw = meta.get("EXCLUDED_SECTORS") or "[]"
+        excluded_sectors = json.loads(raw) if isinstance(raw, str) else raw
+    except Exception:
+        excluded_sectors = []
+
+    # Build risk factor summary
+    risk_factors = []
+    recommendations = []
+
+    # --- Market risk ---
+    if risk_focus in ("market", "all"):
+        equity_pct = sum(
+            float(r["PCT"] or 0) for r in asset_classes if "equity" in (r["ID"] or "").lower()
+        )
+        if equity_pct > 60:
+            risk_factors.append(
+                f"High equity concentration: {equity_pct:.1f}% of portfolio is in equities."
+            )
+            for h in _HEDGE_CATALOGUE["market"]:
+                if esg_mandate and h["ticker"] in ("SQQQ",):
+                    continue  # Skip leveraged products for ESG/conservative accounts
+                recommendations.append(
+                    {**h, "hedge_dimension": "market", "trigger": f"equity_pct={equity_pct:.1f}%"}
+                )
+
+        if high_risk:
+            high_risk_pct = sum(float(r["PCT"] or 0) for r in high_risk)
+            risk_factors.append(
+                f"{len(high_risk)} high-risk positions (risk_rating ≥ 7) totalling {high_risk_pct:.1f}% of portfolio."
+            )
+            recommendations.append(
+                {
+                    "ticker": "GLD",
+                    "name": "SPDR Gold Shares",
+                    "type": "Safe Haven",
+                    "rationale": f"Gold allocation offsets tail risk from {len(high_risk)} high-rated positions.",
+                    "risk_level": "low",
+                    "hedge_dimension": "market",
+                    "trigger": f"high_risk_positions={len(high_risk)}",
+                }
+            )
+
+    # --- Sector risk ---
+    if risk_focus in ("sector", "all") and sectors:
+        top_sector = sectors[0]
+        top_sector_name = top_sector["ID"] or "Unknown"
+        top_sector_pct = float(top_sector["PCT"] or 0)
+        if top_sector_pct > 30:
+            risk_factors.append(
+                f"Sector concentration: {top_sector_name} represents {top_sector_pct:.1f}% of portfolio."
+            )
+            sector_hedges = _HEDGE_CATALOGUE["sector"].get(
+                top_sector_name, _HEDGE_CATALOGUE["sector"]["DEFAULT"]
+            )
+            for h in sector_hedges:
+                if esg_mandate and h["risk_level"] == "high":
+                    continue
+                if top_sector_name in excluded_sectors:
+                    continue
+                recommendations.append(
+                    {
+                        **h,
+                        "hedge_dimension": "sector",
+                        "trigger": f"{top_sector_name}={top_sector_pct:.1f}%",
+                    }
+                )
+
+    # --- Regional risk ---
+    if risk_focus in ("regional", "all") and regions:
+        top_region = regions[0]
+        top_region_name = top_region["ID"] or "Unknown"
+        top_region_pct = float(top_region["PCT"] or 0)
+        if top_region_pct > 50:
+            risk_factors.append(
+                f"Regional concentration: {top_region_name} represents {top_region_pct:.1f}% of portfolio."
+            )
+            region_hedges = _HEDGE_CATALOGUE["regional"].get(
+                top_region_name, _HEDGE_CATALOGUE["regional"]["DEFAULT"]
+            )
+            for h in region_hedges:
+                recommendations.append(
+                    {
+                        **h,
+                        "hedge_dimension": "regional",
+                        "trigger": f"{top_region_name}={top_region_pct:.1f}%",
+                    }
+                )
+
+    # --- Currency risk ---
+    if risk_focus in ("currency", "all"):
+        intl_pct = sum(
+            float(r["PCT"] or 0)
+            for r in regions
+            if (r["ID"] or "").lower() not in ("north america", "usa", "us")
+        )
+        if intl_pct > 25:
+            risk_factors.append(
+                f"International exposure: {intl_pct:.1f}% of portfolio is outside North America, creating FX risk."
+            )
+            for h in _HEDGE_CATALOGUE["currency"]:
+                recommendations.append(
+                    {**h, "hedge_dimension": "currency", "trigger": f"intl_pct={intl_pct:.1f}%"}
+                )
+
+    # De-duplicate by ticker, keeping first occurrence
+    seen_tickers = set()
+    unique_recommendations = []
+    for r in recommendations:
+        if r["ticker"] not in seen_tickers:
+            seen_tickers.add(r["ticker"])
+            unique_recommendations.append(r)
+
+    return {
+        "account_id": account_id,
+        "risk_profile": risk_profile,
+        "esg_mandate": esg_mandate,
+        "risk_focus": risk_focus,
+        "portfolio_summary": {
+            "total_holdings": len(holdings),
+            "high_risk_positions": len(high_risk),
+            "sector_breakdown": [{"sector": r["ID"], "pct": r["PCT"]} for r in sectors],
+            "region_breakdown": [{"region": r["ID"], "pct": r["PCT"]} for r in regions],
+            "asset_class_breakdown": [
+                {"asset_class": r["ID"], "pct": r["PCT"]} for r in asset_classes
+            ],
+        },
+        "risk_factors_identified": risk_factors,
+        "hedge_recommendations": unique_recommendations,
+        "disclaimer": (
+            "These recommendations are generated algorithmically for illustrative purposes only. "
+            "All hedging decisions should be reviewed by a qualified financial advisor and assessed "
+            "for suitability against the client's investment policy statement."
+        ),
+    }
+
+
 def _convergent_search(conn, embedding_model, args, query_logger):
     """Convergent query: Relational + Graph + Vector + Spatial in a single SQL statement.
 
diff --git a/apps/finance-ai-agent-demo/backend/pytest.ini b/apps/finance-ai-agent-demo/backend/pytest.ini
new file mode 100644
index 00000000..9855d94e
--- /dev/null
+++ b/apps/finance-ai-agent-demo/backend/pytest.ini
@@ -0,0 +1,6 @@
+[pytest]
+testpaths = tests
+python_files = test_*.py
+python_classes = Test*
+python_functions = test_*
+addopts = -v --tb=short
diff --git a/apps/finance-ai-agent-demo/backend/requirements.txt b/apps/finance-ai-agent-demo/backend/requirements.txt
index 19ef71c5..dbfdf3b5 100644
--- a/apps/finance-ai-agent-demo/backend/requirements.txt
+++ b/apps/finance-ai-agent-demo/backend/requirements.txt
@@ -24,3 +24,5 @@ pandas>=2.0
 pydantic>=2.0
 python-dotenv>=1.0
 tiktoken>=0.7
+pytest>=8.0
+pytest-mock>=3.12
diff --git a/apps/finance-ai-agent-demo/backend/tests/__init__.py b/apps/finance-ai-agent-demo/backend/tests/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/apps/finance-ai-agent-demo/backend/tests/conftest.py b/apps/finance-ai-agent-demo/backend/tests/conftest.py
new file mode 100644
index 00000000..9d60e49e
--- /dev/null
+++ b/apps/finance-ai-agent-demo/backend/tests/conftest.py
@@ -0,0 +1,270 @@
+"""Shared pytest fixtures for the finance-ai-agent backend test suite."""
+
+import pytest
+
+# ---------------------------------------------------------------------------
+# Minimal portfolio rows as returned by _suggest_portfolio_hedge's SQL query
+# ---------------------------------------------------------------------------
+
+
+def _holding(
+    holding_id,
+    instrument_name,
+    ticker,
+    sector,
+    region,
+    asset_class,
+    risk_rating,
+    pct,
+    risk_profile="moderate",
+    esg_mandate=None,
+    max_position="0.10",
+    excluded_sectors=None,
+):
+    return {
+        "ROW_TYPE": "HOLDING",
+        "ID": holding_id,
+        "LABEL": instrument_name,
+        "TICKER": ticker,
+        "SECTOR": sector,
+        "REGION": region,
+        "ASSET_CLASS": asset_class,
+        "RISK_RATING": risk_rating,
+        "PCT": pct,
+        "RISK_PROFILE": risk_profile,
+        "ESG_MANDATE": esg_mandate,
+        "MAX_POSITION": max_position,
+        "EXCLUDED_SECTORS": excluded_sectors or "[]",
+    }
+
+
+def _sector(name, pct):
+    return {
+        "ROW_TYPE": "SECTOR",
+        "ID": name,
+        "LABEL": name,
+        "TICKER": None,
+        "SECTOR": None,
+        "REGION": None,
+        "ASSET_CLASS": None,
+        "RISK_RATING": None,
+        "PCT": pct,
+        "RISK_PROFILE": None,
+        "ESG_MANDATE": None,
+        "MAX_POSITION": None,
+        "EXCLUDED_SECTORS": None,
+    }
+
+
+def _region(name, pct):
+    return {
+        "ROW_TYPE": "REGION",
+        "ID": name,
+        "LABEL": name,
+        "TICKER": None,
+        "SECTOR": None,
+        "REGION": None,
+        "ASSET_CLASS": None,
+        "RISK_RATING": None,
+        "PCT": pct,
+        "RISK_PROFILE": None,
+        "ESG_MANDATE": None,
+        "MAX_POSITION": None,
+        "EXCLUDED_SECTORS": None,
+    }
+
+
+def _asset_class(name, pct):
+    return {
+        "ROW_TYPE": "ASSET_CLASS",
+        "ID": name,
+        "LABEL": name,
+        "TICKER": None,
+        "SECTOR": None,
+        "REGION": None,
+        "ASSET_CLASS": None,
+        "RISK_RATING": None,
+        "PCT": pct,
+        "RISK_PROFILE": None,
+        "ESG_MANDATE": None,
+        "MAX_POSITION": None,
+        "EXCLUDED_SECTORS": None,
+    }
+
+
+def _high_risk(holding_id, instrument_name, ticker, sector, region, risk_rating, pct):
+    return {
+        "ROW_TYPE": "HIGH_RISK",
+        "ID": holding_id,
+        "LABEL": instrument_name,
+        "TICKER": ticker,
+        "SECTOR": sector,
+        "REGION": region,
+        "ASSET_CLASS": None,
+        "RISK_RATING": risk_rating,
+        "PCT": pct,
+        "RISK_PROFILE": None,
+        "ESG_MANDATE": None,
+        "MAX_POSITION": None,
+        "EXCLUDED_SECTORS": None,
+    }
+
+
+@pytest.fixture
+def tech_heavy_rows():
+    """Portfolio that is tech-heavy (40% sector) and equity-heavy (80% equities),
+    located primarily in North America (70%), with two high-risk positions."""
+    return [
+        _holding(
+            "H001",
+            "Apple Inc",
+            "AAPL",
+            "Technology",
+            "North America",
+            "Equity",
+            6,
+            25.0,
+            risk_profile="aggressive",
+        ),
+        _holding(
+            "H002",
+            "Microsoft Corp",
+            "MSFT",
+            "Technology",
+            "North America",
+            "Equity",
+            5,
+            15.0,
+            risk_profile="aggressive",
+        ),
+        _holding(
+            "H003",
+            "ExxonMobil",
+            "XOM",
+            "Energy",
+            "North America",
+            "Equity",
+            4,
+            20.0,
+            risk_profile="aggressive",
+        ),
+        _holding(
+            "H004",
+            "Riskco Ltd",
+            "RSK",
+            "Technology",
+            "Europe",
+            "Equity",
+            8,
+            10.0,
+            risk_profile="aggressive",
+        ),
+        _holding(
+            "H005",
+            "DangerFund",
+            "DNG",
+            "Financials",
+            "Asia",
+            "Equity",
+            9,
+            10.0,
+            risk_profile="aggressive",
+        ),
+        _holding(
+            "H006",
+            "Safe Bond A",
+            "SBA",
+            "Government",
+            "North America",
+            "Bond",
+            2,
+            20.0,
+            risk_profile="aggressive",
+        ),
+        _sector("Technology", 40.0),
+        _sector("Energy", 20.0),
+        _sector("Government", 20.0),
+        _sector("Financials", 10.0),
+        _region("North America", 65.0),
+        _region("Europe", 20.0),
+        _region("Asia", 15.0),
+        _asset_class("Equity", 80.0),
+        _asset_class("Bond", 20.0),
+        _high_risk("H004", "Riskco Ltd", "RSK", "Technology", "Europe", 8, 10.0),
+        _high_risk("H005", "DangerFund", "DNG", "Financials", "Asia", 9, 10.0),
+    ]
+
+
+@pytest.fixture
+def esg_rows():
+    """Portfolio with ESG mandate set — leveraged/high-risk instruments should be filtered."""
+    return [
+        _holding(
+            "H001",
+            "Green Energy ETF",
+            "GRN",
+            "Energy",
+            "North America",
+            "Equity",
+            3,
+            70.0,
+            risk_profile="conservative",
+            esg_mandate="yes",
+        ),
+        _holding(
+            "H002",
+            "Clean Tech Fund",
+            "CLT",
+            "Technology",
+            "North America",
+            "Equity",
+            4,
+            30.0,
+            risk_profile="conservative",
+            esg_mandate="yes",
+        ),
+        _sector("Energy", 70.0),
+        _sector("Technology", 30.0),
+        _region("North America", 100.0),
+        _asset_class("Equity", 100.0),
+    ]
+
+
+@pytest.fixture
+def balanced_rows():
+    """Well-diversified portfolio — should trigger few or no risk factors."""
+    return [
+        _holding("H001", "US Equity Fund", "USQ", "Financials", "North America", "Equity", 3, 20.0),
+        _holding("H002", "EU Bond Fund", "EUB", "Government", "Europe", "Bond", 2, 20.0),
+        _holding("H003", "Asia Growth", "ASG", "Technology", "Asia", "Equity", 4, 20.0),
+        _holding("H004", "Gold ETF", "GLD", "Commodities", "North America", "Commodity", 2, 20.0),
+        _holding("H005", "EM Equity", "EMQ", "Financials", "Asia", "Equity", 5, 20.0),
+        _sector("Financials", 25.0),
+        _sector("Government", 20.0),
+        _sector("Technology", 20.0),
+        _sector("Commodities", 20.0),
+        _region("North America", 40.0),
+        _region("Europe", 20.0),
+        _region("Asia", 40.0),
+        _asset_class("Equity", 60.0),
+        _asset_class("Bond", 20.0),
+        _asset_class("Commodity", 20.0),
+    ]
+
+
+@pytest.fixture
+def intl_heavy_rows():
+    """Portfolio with 60% outside North America — should trigger currency hedge."""
+    return [
+        _holding("H001", "EU Stocks", "EUS", "Financials", "Europe", "Equity", 4, 35.0),
+        _holding("H002", "Japan Growth", "JPG", "Technology", "Asia", "Equity", 5, 25.0),
+        _holding("H003", "US Bonds", "USB", "Government", "North America", "Bond", 2, 40.0),
+        _sector("Financials", 35.0),
+        _sector("Technology", 25.0),
+        _sector("Government", 40.0),
+        _region("Europe", 35.0),
+        _region("Asia", 25.0),
+        _region("North America", 40.0),
+        _asset_class("Equity", 60.0),
+        _asset_class("Bond", 40.0),
+    ]
diff --git a/apps/finance-ai-agent-demo/backend/tests/test_hedge_recommendations.py b/apps/finance-ai-agent-demo/backend/tests/test_hedge_recommendations.py
new file mode 100644
index 00000000..b5c144c2
--- /dev/null
+++ b/apps/finance-ai-agent-demo/backend/tests/test_hedge_recommendations.py
@@ -0,0 +1,389 @@
+"""Unit tests for the hedge recommendation engine (_build_hedge_recommendations).
+
+All tests run without a database connection — they call the pure-Python
+recommendation logic directly with pre-built row fixtures.
+"""
+
+import json
+import os
+import sys
+
+# Ensure the backend package root is on the path so imports resolve
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+from agent.tools import _build_hedge_recommendations
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+
+def tickers(recommendations):
+    return [r["ticker"] for r in recommendations]
+
+
+def dimensions(recommendations):
+    return {r["hedge_dimension"] for r in recommendations}
+
+
+# ---------------------------------------------------------------------------
+# Output structure
+# ---------------------------------------------------------------------------
+
+
+class TestOutputStructure:
+    def test_returns_dict_with_required_keys(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "all")
+        for key in (
+            "account_id",
+            "risk_profile",
+            "esg_mandate",
+            "risk_focus",
+            "portfolio_summary",
+            "risk_factors_identified",
+            "hedge_recommendations",
+            "disclaimer",
+        ):
+            assert key in result, f"Missing key: {key}"
+
+    def test_account_id_preserved(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-042", "all")
+        assert result["account_id"] == "ACC-042"
+
+    def test_risk_focus_preserved(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "sector")
+        assert result["risk_focus"] == "sector"
+
+    def test_portfolio_summary_contains_breakdowns(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "all")
+        summary = result["portfolio_summary"]
+        assert isinstance(summary["sector_breakdown"], list)
+        assert isinstance(summary["region_breakdown"], list)
+        assert isinstance(summary["asset_class_breakdown"], list)
+        assert summary["total_holdings"] == 6
+        assert summary["high_risk_positions"] == 2
+
+    def test_disclaimer_present_and_non_empty(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "all")
+        assert len(result["disclaimer"]) > 20
+
+    def test_recommendations_are_list(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "all")
+        assert isinstance(result["hedge_recommendations"], list)
+
+    def test_each_recommendation_has_required_fields(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "all")
+        for rec in result["hedge_recommendations"]:
+            for field in (
+                "ticker",
+                "name",
+                "type",
+                "rationale",
+                "risk_level",
+                "hedge_dimension",
+                "trigger",
+            ):
+                assert field in rec, f"Recommendation missing field: {field}"
+
+    def test_no_duplicate_tickers(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "all")
+        seen = [r["ticker"] for r in result["hedge_recommendations"]]
+        assert len(seen) == len(set(seen)), f"Duplicate tickers found: {seen}"
+
+    def test_json_serialisable(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "all")
+        # Should not raise
+        json.dumps(result)
+
+
+# ---------------------------------------------------------------------------
+# Market risk detection
+# ---------------------------------------------------------------------------
+
+
+class TestMarketRiskDetection:
+    def test_equity_heavy_triggers_market_risk_factor(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "market")
+        assert any("equity" in f.lower() for f in result["risk_factors_identified"])
+
+    def test_market_hedge_instruments_included_for_equity_heavy(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "market")
+        t = tickers(result["hedge_recommendations"])
+        # At least one of the core market hedges must appear
+        assert any(tk in t for tk in ("SH", "GLD", "TLT")), f"No market hedge found: {t}"
+
+    def test_high_risk_positions_trigger_market_risk_factor(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "market")
+        assert any("high-risk" in f.lower() for f in result["risk_factors_identified"])
+
+    def test_high_risk_positions_trigger_gold_recommendation(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "market")
+        assert "GLD" in tickers(result["hedge_recommendations"])
+
+    def test_balanced_portfolio_no_market_risk_factor(self, balanced_rows):
+        result = _build_hedge_recommendations(balanced_rows, "ACC-001", "market")
+        # Equity is only 60% — below the 60% threshold, no market risk factor
+        assert not any("equity" in f.lower() for f in result["risk_factors_identified"])
+
+    def test_market_focus_only_returns_market_dimension(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "market")
+        dims = dimensions(result["hedge_recommendations"])
+        assert dims <= {"market"}, f"Unexpected dimensions: {dims}"
+
+
+# ---------------------------------------------------------------------------
+# Sector risk detection
+# ---------------------------------------------------------------------------
+
+
+class TestSectorRiskDetection:
+    def test_tech_overweight_triggers_sector_risk_factor(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "sector")
+        assert any("technology" in f.lower() for f in result["risk_factors_identified"])
+
+    def test_tech_overweight_triggers_tech_hedges(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "sector")
+        # Tech hedges include PUT (QQQ puts) or REK
+        t = tickers(result["hedge_recommendations"])
+        assert any(tk in t for tk in ("PUT", "REK", "VXUS")), f"No sector hedge found: {t}"
+
+    def test_balanced_portfolio_no_sector_risk_factor(self, balanced_rows):
+        result = _build_hedge_recommendations(balanced_rows, "ACC-001", "sector")
+        # No sector > 30%, so no sector risk factor expected
+        assert not any("sector" in f.lower() or "%" in f for f in result["risk_factors_identified"])
+
+    def test_sector_focus_only_returns_sector_dimension(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "sector")
+        dims = dimensions(result["hedge_recommendations"])
+        assert dims <= {"sector"}, f"Unexpected dimensions: {dims}"
+
+
+# ---------------------------------------------------------------------------
+# Regional risk detection
+# ---------------------------------------------------------------------------
+
+
+class TestRegionalRiskDetection:
+    def test_na_heavy_triggers_regional_risk_factor(self, tech_heavy_rows):
+        # North America is 65% — above the 50% threshold
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "regional")
+        assert any("north america" in f.lower() for f in result["risk_factors_identified"])
+
+    def test_na_heavy_triggers_geographic_diversification_hedge(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "regional")
+        t = tickers(result["hedge_recommendations"])
+        assert any(tk in t for tk in ("EFA", "ACWX")), f"No regional hedge found: {t}"
+
+    def test_balanced_no_regional_risk_factor(self, balanced_rows):
+        result = _build_hedge_recommendations(balanced_rows, "ACC-001", "regional")
+        # No region > 50% in balanced_rows
+        assert not result["risk_factors_identified"]
+
+    def test_regional_focus_only_returns_regional_dimension(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "regional")
+        dims = dimensions(result["hedge_recommendations"])
+        assert dims <= {"regional"}, f"Unexpected dimensions: {dims}"
+
+
+# ---------------------------------------------------------------------------
+# Currency risk detection
+# ---------------------------------------------------------------------------
+
+
+class TestCurrencyRiskDetection:
+    def test_intl_heavy_triggers_currency_risk_factor(self, intl_heavy_rows):
+        result = _build_hedge_recommendations(intl_heavy_rows, "ACC-001", "currency")
+        assert any(
+            "fx" in f.lower() or "international" in f.lower()
+            for f in result["risk_factors_identified"]
+        )
+
+    def test_intl_heavy_includes_currency_hedge_instruments(self, intl_heavy_rows):
+        result = _build_hedge_recommendations(intl_heavy_rows, "ACC-001", "currency")
+        t = tickers(result["hedge_recommendations"])
+        assert any(tk in t for tk in ("UUP", "FXE")), f"No currency hedge found: {t}"
+
+    def test_na_only_no_currency_risk(self, esg_rows):
+        # esg_rows is 100% North America
+        result = _build_hedge_recommendations(esg_rows, "ACC-001", "currency")
+        assert not result["risk_factors_identified"]
+
+    def test_currency_focus_only_returns_currency_dimension(self, intl_heavy_rows):
+        result = _build_hedge_recommendations(intl_heavy_rows, "ACC-001", "currency")
+        dims = dimensions(result["hedge_recommendations"])
+        assert dims <= {"currency"}, f"Unexpected dimensions: {dims}"
+
+
+# ---------------------------------------------------------------------------
+# ESG mandate filtering
+# ---------------------------------------------------------------------------
+
+
+class TestEsgMandateFiltering:
+    def test_esg_mandate_detected_from_rows(self, esg_rows):
+        result = _build_hedge_recommendations(esg_rows, "ACC-001", "all")
+        assert result["esg_mandate"] is True
+
+    def test_no_esg_mandate_when_field_absent(self, tech_heavy_rows):
+        # tech_heavy_rows have esg_mandate=None
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "all")
+        assert result["esg_mandate"] is False
+
+    def test_esg_filters_out_sqqq(self, esg_rows):
+        # Energy is 70% — triggers market risk; SQQQ should be absent for ESG accounts
+        result = _build_hedge_recommendations(esg_rows, "ACC-001", "market")
+        assert "SQQQ" not in tickers(result["hedge_recommendations"])
+
+    def test_esg_filters_high_risk_level_sector_hedges(self, esg_rows):
+        # Sector hedges with risk_level='high' should be excluded for ESG accounts
+        result = _build_hedge_recommendations(esg_rows, "ACC-001", "sector")
+        for rec in result["hedge_recommendations"]:
+            assert rec["risk_level"] != "high", (
+                f"High-risk instrument {rec['ticker']} slipped through ESG filter"
+            )
+
+
+# ---------------------------------------------------------------------------
+# risk_focus scoping
+# ---------------------------------------------------------------------------
+
+
+class TestRiskFocusScoping:
+    def test_all_can_return_multiple_dimensions(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "all")
+        dims = dimensions(result["hedge_recommendations"])
+        # With tech_heavy_rows, at minimum market + sector + regional should fire
+        assert len(dims) >= 2, f"Expected multiple dimensions, got: {dims}"
+
+    def test_market_focus_excludes_sector_dimension(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "market")
+        assert "sector" not in dimensions(result["hedge_recommendations"])
+
+    def test_sector_focus_excludes_market_dimension(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "sector")
+        assert "market" not in dimensions(result["hedge_recommendations"])
+
+    def test_regional_focus_excludes_market_dimension(self, tech_heavy_rows):
+        result = _build_hedge_recommendations(tech_heavy_rows, "ACC-001", "regional")
+        assert "market" not in dimensions(result["hedge_recommendations"])
+
+    def test_currency_focus_excludes_sector_dimension(self, intl_heavy_rows):
+        result = _build_hedge_recommendations(intl_heavy_rows, "ACC-001", "currency")
+        assert "sector" not in dimensions(result["hedge_recommendations"])
+
+
+# ---------------------------------------------------------------------------
+# Empty / edge cases
+# ---------------------------------------------------------------------------
+
+
+class TestEdgeCases:
+    def test_empty_rows_returns_no_risk_factors_or_recommendations(self):
+        # No holdings at all — _suggest_portfolio_hedge would catch this upstream,
+        # but _build_hedge_recommendations should handle gracefully
+        result = _build_hedge_recommendations([], "ACC-999", "all")
+        assert result["risk_factors_identified"] == []
+        assert result["hedge_recommendations"] == []
+
+    def test_none_pct_values_do_not_crash(self):
+        rows = [
+            {
+                "ROW_TYPE": "HOLDING",
+                "ID": "H001",
+                "LABEL": "Foo",
+                "TICKER": "FOO",
+                "SECTOR": "Technology",
+                "REGION": "North America",
+                "ASSET_CLASS": "Equity",
+                "RISK_RATING": 5,
+                "PCT": None,
+                "RISK_PROFILE": "moderate",
+                "ESG_MANDATE": None,
+                "MAX_POSITION": "0.10",
+                "EXCLUDED_SECTORS": "[]",
+            },
+            {
+                "ROW_TYPE": "ASSET_CLASS",
+                "ID": "Equity",
+                "LABEL": "Equity",
+                "TICKER": None,
+                "SECTOR": None,
+                "REGION": None,
+                "ASSET_CLASS": None,
+                "RISK_RATING": None,
+                "PCT": None,
+                "RISK_PROFILE": None,
+                "ESG_MANDATE": None,
+                "MAX_POSITION": None,
+                "EXCLUDED_SECTORS": None,
+            },
+        ]
+        # Should not raise even with None PCT values
+        result = _build_hedge_recommendations(rows, "ACC-999", "all")
+        assert isinstance(result, dict)
+
+    def test_malformed_excluded_sectors_does_not_crash(self):
+        rows = [
+            {
+                "ROW_TYPE": "HOLDING",
+                "ID": "H001",
+                "LABEL": "Foo",
+                "TICKER": "FOO",
+                "SECTOR": "Technology",
+                "REGION": "North America",
+                "ASSET_CLASS": "Equity",
+                "RISK_RATING": 5,
+                "PCT": 50.0,
+                "RISK_PROFILE": "moderate",
+                "ESG_MANDATE": None,
+                "MAX_POSITION": "0.10",
+                "EXCLUDED_SECTORS": "NOT_VALID_JSON",
+            },
+            {
+                "ROW_TYPE": "SECTOR",
+                "ID": "Technology",
+                "LABEL": "Technology",
+                "TICKER": None,
+                "SECTOR": None,
+                "REGION": None,
+                "ASSET_CLASS": None,
+                "RISK_RATING": None,
+                "PCT": 50.0,
+                "RISK_PROFILE": None,
+                "ESG_MANDATE": None,
+                "MAX_POSITION": None,
+                "EXCLUDED_SECTORS": None,
+            },
+            {
+                "ROW_TYPE": "REGION",
+                "ID": "North America",
+                "LABEL": "North America",
+                "TICKER": None,
+                "SECTOR": None,
+                "REGION": None,
+                "ASSET_CLASS": None,
+                "RISK_RATING": None,
+                "PCT": 100.0,
+                "RISK_PROFILE": None,
+                "ESG_MANDATE": None,
+                "MAX_POSITION": None,
+                "EXCLUDED_SECTORS": None,
+            },
+            {
+                "ROW_TYPE": "ASSET_CLASS",
+                "ID": "Equity",
+                "LABEL": "Equity",
+                "TICKER": None,
+                "SECTOR": None,
+                "REGION": None,
+                "ASSET_CLASS": None,
+                "RISK_RATING": None,
+                "PCT": 100.0,
+                "RISK_PROFILE": None,
+                "ESG_MANDATE": None,
+                "MAX_POSITION": None,
+                "EXCLUDED_SECTORS": None,
+            },
+        ]
+        result = _build_hedge_recommendations(rows, "ACC-999", "all")
+        assert isinstance(result, dict)
diff --git a/apps/finance-ai-agent-demo/backend/tests/test_suggest_portfolio_hedge_integration.py b/apps/finance-ai-agent-demo/backend/tests/test_suggest_portfolio_hedge_integration.py
new file mode 100644
index 00000000..345ce7ab
--- /dev/null
+++ b/apps/finance-ai-agent-demo/backend/tests/test_suggest_portfolio_hedge_integration.py
@@ -0,0 +1,209 @@
+"""Integration-style tests for _suggest_portfolio_hedge.
+
+These tests call _suggest_portfolio_hedge directly with a mock DB connection
+that returns controlled row data — no real Oracle instance required.
+The goal is to verify the full pipeline: SQL execution → row parsing →
+_build_hedge_recommendations → JSON output.
+"""
+
+import json
+import os
+import sys
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+
+# ---------------------------------------------------------------------------
+# Minimal mock connection and execute_query that return fixture rows
+# ---------------------------------------------------------------------------
+
+
+class MockQueryLogger:
+    def __init__(self):
+        self.calls = []
+
+    def log(self, *args, **kwargs):
+        self.calls.append((args, kwargs))
+
+
+def make_execute_query_stub(rows):
+    """Return a drop-in for execute_query that yields `rows` with column names."""
+    columns = [
+        "ROW_TYPE",
+        "ID",
+        "LABEL",
+        "TICKER",
+        "SECTOR",
+        "REGION",
+        "ASSET_CLASS",
+        "RISK_RATING",
+        "PCT",
+        "RISK_PROFILE",
+        "ESG_MANDATE",
+        "MAX_POSITION",
+        "EXCLUDED_SECTORS",
+    ]
+
+    def _execute_query(conn, sql, params, query_logger, description=""):
+        # Convert dict rows to tuples matching column order
+        tuple_rows = [tuple(r.get(c) for c in columns) for r in rows]
+        return tuple_rows, columns
+
+    return _execute_query
+
+
+# ---------------------------------------------------------------------------
+# Tests
+# ---------------------------------------------------------------------------
+
+
+class TestSuggestPortfolioHedgeOutput:
+    def test_returns_valid_json_string(self, tech_heavy_rows, monkeypatch):
+        import agent.tools as tools_module
+
+        monkeypatch.setattr("agent.tools.execute_query", make_execute_query_stub(tech_heavy_rows))
+
+        result_str = tools_module._suggest_portfolio_hedge(
+            conn=object(),
+            args={"account_id": "ACC-001", "risk_focus": "all"},
+            query_logger=MockQueryLogger(),
+        )
+        result = json.loads(result_str)
+        assert isinstance(result, dict)
+
+    def test_result_contains_hedge_recommendations(self, tech_heavy_rows, monkeypatch):
+        import agent.tools as tools_module
+
+        monkeypatch.setattr("agent.tools.execute_query", make_execute_query_stub(tech_heavy_rows))
+
+        result = json.loads(
+            tools_module._suggest_portfolio_hedge(
+                conn=object(),
+                args={"account_id": "ACC-001", "risk_focus": "all"},
+                query_logger=MockQueryLogger(),
+            )
+        )
+        assert len(result["hedge_recommendations"]) > 0
+
+    def test_no_holdings_returns_error_message(self, monkeypatch):
+        import agent.tools as tools_module
+
+        monkeypatch.setattr("agent.tools.execute_query", make_execute_query_stub([]))
+
+        result = tools_module._suggest_portfolio_hedge(
+            conn=object(),
+            args={"account_id": "ACC-999"},
+            query_logger=MockQueryLogger(),
+        )
+        assert "No holdings found" in result
+        assert "ACC-999" in result
+
+    def test_default_risk_focus_is_all(self, tech_heavy_rows, monkeypatch):
+        import agent.tools as tools_module
+
+        monkeypatch.setattr("agent.tools.execute_query", make_execute_query_stub(tech_heavy_rows))
+
+        # Omit risk_focus — should default to 'all'
+        result = json.loads(
+            tools_module._suggest_portfolio_hedge(
+                conn=object(),
+                args={"account_id": "ACC-001"},
+                query_logger=MockQueryLogger(),
+            )
+        )
+        assert result["risk_focus"] == "all"
+
+    def test_query_logger_is_called(self, tech_heavy_rows, monkeypatch):
+        import agent.tools as tools_module
+
+        logger = MockQueryLogger()
+        called = []
+
+        def _stub(conn, sql, params, query_logger, description=""):
+            called.append(description)
+            columns = [
+                "ROW_TYPE",
+                "ID",
+                "LABEL",
+                "TICKER",
+                "SECTOR",
+                "REGION",
+                "ASSET_CLASS",
+                "RISK_RATING",
+                "PCT",
+                "RISK_PROFILE",
+                "ESG_MANDATE",
+                "MAX_POSITION",
+                "EXCLUDED_SECTORS",
+            ]
+            return [tuple(r.get(c) for c in columns) for r in tech_heavy_rows], columns
+
+        monkeypatch.setattr("agent.tools.execute_query", _stub)
+        tools_module._suggest_portfolio_hedge(
+            conn=object(),
+            args={"account_id": "ACC-001"},
+            query_logger=logger,
+        )
+        assert any("ACC-001" in d for d in called)
+
+    def test_esg_portfolio_excludes_leveraged_products(self, esg_rows, monkeypatch):
+        import agent.tools as tools_module
+
+        monkeypatch.setattr("agent.tools.execute_query", make_execute_query_stub(esg_rows))
+
+        result = json.loads(
+            tools_module._suggest_portfolio_hedge(
+                conn=object(),
+                args={"account_id": "ACC-ESG", "risk_focus": "all"},
+                query_logger=MockQueryLogger(),
+            )
+        )
+        rec_tickers = [r["ticker"] for r in result["hedge_recommendations"]]
+        assert "SQQQ" not in rec_tickers
+
+    def test_market_focus_filters_non_market_dimensions(self, tech_heavy_rows, monkeypatch):
+        import agent.tools as tools_module
+
+        monkeypatch.setattr("agent.tools.execute_query", make_execute_query_stub(tech_heavy_rows))
+
+        result = json.loads(
+            tools_module._suggest_portfolio_hedge(
+                conn=object(),
+                args={"account_id": "ACC-001", "risk_focus": "market"},
+                query_logger=MockQueryLogger(),
+            )
+        )
+        dims = {r["hedge_dimension"] for r in result["hedge_recommendations"]}
+        assert dims <= {"market"}
+
+    def test_account_id_in_params_passed_to_sql(self, tech_heavy_rows, monkeypatch):
+        import agent.tools as tools_module
+
+        received_params = {}
+
+        def _stub(conn, sql, params, query_logger, description=""):
+            received_params.update(params)
+            columns = [
+                "ROW_TYPE",
+                "ID",
+                "LABEL",
+                "TICKER",
+                "SECTOR",
+                "REGION",
+                "ASSET_CLASS",
+                "RISK_RATING",
+                "PCT",
+                "RISK_PROFILE",
+                "ESG_MANDATE",
+                "MAX_POSITION",
+                "EXCLUDED_SECTORS",
+            ]
+            return [tuple(r.get(c) for c in columns) for r in tech_heavy_rows], columns
+
+        monkeypatch.setattr("agent.tools.execute_query", _stub)
+        tools_module._suggest_portfolio_hedge(
+            conn=object(),
+            args={"account_id": "ACC-007"},
+            query_logger=MockQueryLogger(),
+        )
+        assert received_params.get("account_id") == "ACC-007"
diff --git a/apps/finance-ai-agent-demo/backend/tests/test_tool_schema.py b/apps/finance-ai-agent-demo/backend/tests/test_tool_schema.py
new file mode 100644
index 00000000..abea0677
--- /dev/null
+++ b/apps/finance-ai-agent-demo/backend/tests/test_tool_schema.py
@@ -0,0 +1,124 @@
+"""Tests for the suggest_portfolio_hedge tool schema registration.
+
+Verifies the tool is correctly declared in TOOL_SCHEMAS and PRELOADED_TOOLS
+so the LLM will always have access to it.
+"""
+
+import os
+import sys
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+from agent.tools import PRELOADED_TOOLS, TOOL_SCHEMAS
+
+
+def _find_tool(tools, name):
+    return next((t for t in tools if t["function"]["name"] == name), None)
+
+
+class TestToolSchemaRegistration:
+    def test_tool_present_in_tool_schemas(self):
+        tool = _find_tool(TOOL_SCHEMAS, "suggest_portfolio_hedge")
+        assert tool is not None, "suggest_portfolio_hedge missing from TOOL_SCHEMAS"
+
+    def test_tool_present_in_preloaded_tools(self):
+        tool = _find_tool(PRELOADED_TOOLS, "suggest_portfolio_hedge")
+        assert tool is not None, "suggest_portfolio_hedge missing from PRELOADED_TOOLS"
+
+    def test_tool_has_correct_type(self):
+        tool = _find_tool(TOOL_SCHEMAS, "suggest_portfolio_hedge")
+        assert tool["type"] == "function"
+
+    def test_account_id_is_required_parameter(self):
+        tool = _find_tool(TOOL_SCHEMAS, "suggest_portfolio_hedge")
+        params = tool["function"]["parameters"]
+        assert "account_id" in params["required"]
+        assert "account_id" in params["properties"]
+
+    def test_risk_focus_is_optional(self):
+        tool = _find_tool(TOOL_SCHEMAS, "suggest_portfolio_hedge")
+        params = tool["function"]["parameters"]
+        assert "risk_focus" in params["properties"]
+        assert "risk_focus" not in params.get("required", [])
+
+    def test_risk_focus_enum_values(self):
+        tool = _find_tool(TOOL_SCHEMAS, "suggest_portfolio_hedge")
+        enum_vals = tool["function"]["parameters"]["properties"]["risk_focus"]["enum"]
+        assert set(enum_vals) == {"market", "sector", "regional", "currency", "all"}
+
+    def test_description_is_non_empty(self):
+        tool = _find_tool(TOOL_SCHEMAS, "suggest_portfolio_hedge")
+        assert len(tool["function"]["description"]) > 20
+
+    def test_account_id_has_description(self):
+        tool = _find_tool(TOOL_SCHEMAS, "suggest_portfolio_hedge")
+        desc = tool["function"]["parameters"]["properties"]["account_id"].get("description", "")
+        assert len(desc) > 5
+
+    def test_preloaded_tools_is_superset_of_tool_schemas(self):
+        schema_names = {t["function"]["name"] for t in TOOL_SCHEMAS}
+        preloaded_names = {t["function"]["name"] for t in PRELOADED_TOOLS}
+        assert schema_names == preloaded_names
+
+
+class TestToolDispatcherRouting:
+    """Verify that the dispatcher routes suggest_portfolio_hedge without error.
+
+    We mock the DB connection and query_helper so no real Oracle instance is needed.
+    """
+
+    def test_oracle_mode_routes_to_correct_handler(self, monkeypatch):
+        import agent.tools as tools_module
+
+        # Patch execute_query to return empty rows (no DB needed)
+        monkeypatch.setattr(
+            "agent.tools.execute_query",
+            lambda conn, sql, params, query_logger, description="": ([], []),
+        )
+        # Patch ARCH_MODE to converged
+        monkeypatch.setattr(
+            "agent.tools.os.getenv", lambda k, d="": "converged" if k == "ARCH_MODE" else d
+        )
+
+        import types
+
+        fake_config = types.ModuleType("config")
+        fake_config.ARCH_MODE = "converged"
+        monkeypatch.setitem(sys.modules, "config", fake_config)
+
+        execute_tool = tools_module.create_tool_executor(
+            conn=object(),
+            embedding_model=None,
+            memory_manager=None,
+            llm_client=None,
+            query_logger=None,
+        )
+
+        result = execute_tool("suggest_portfolio_hedge", {"account_id": "ACC-001"})
+        # Empty rows → "No holdings found" message
+        assert "No holdings found" in result or isinstance(result, str)
+
+    def test_unknown_tool_returns_error_string(self, monkeypatch):
+        import types
+
+        fake_config = types.ModuleType("config")
+        fake_config.ARCH_MODE = "converged"
+        monkeypatch.setitem(sys.modules, "config", fake_config)
+
+        import agent.tools as tools_module
+
+        monkeypatch.setattr(
+            "agent.tools.execute_query",
+            lambda *a, **kw: ([], []),
+        )
+
+        execute_tool = tools_module.create_tool_executor(
+            conn=object(),
+            embedding_model=None,
+            memory_manager=None,
+            llm_client=None,
+            query_logger=None,
+        )
+
+        result = execute_tool("nonexistent_tool_xyz", {})
+        assert "Error" in result or "Unknown" in result
diff --git a/apps/finance-ai-agent-demo/frontend/package-lock.json b/apps/finance-ai-agent-demo/frontend/package-lock.json
index d6ad4e96..b6bc4576 100644
--- a/apps/finance-ai-agent-demo/frontend/package-lock.json
+++ b/apps/finance-ai-agent-demo/frontend/package-lock.json
@@ -16,15 +16,28 @@
         "socket.io-client": "^4.8.3"
       },
       "devDependencies": {
+        "@testing-library/jest-dom": "^6.9.1",
+        "@testing-library/react": "^16.3.2",
+        "@testing-library/user-event": "^14.6.1",
         "@types/react": "^18.3.3",
         "@types/react-dom": "^18.3.0",
         "@vitejs/plugin-react": "^4.3.1",
+        "@vitest/coverage-v8": "^4.1.7",
         "autoprefixer": "^10.4.19",
+        "jsdom": "^29.1.1",
         "postcss": "^8.4.39",
         "tailwindcss": "^3.4.6",
-        "vite": "^6.4.2"
+        "vite": "^6.4.2",
+        "vitest": "^4.1.7"
       }
     },
+    "node_modules/@adobe/css-tools": {
+      "version": "4.5.0",
+      "resolved": "https://registry.npmjs.org/@adobe/css-tools/-/css-tools-4.5.0.tgz",
+      "integrity": "sha512-6OzddxPio9UiWTCemp4N8cYLV2ZN1ncRnV1cVGtve7dhPOtRkleRyx32GQCYSwDYgaHU3USMm84tNsvKzRCa1Q==",
+      "dev": true,
+      "license": "MIT"
+    },
     "node_modules/@alloc/quick-lru": {
       "version": "5.2.0",
       "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz",
@@ -38,6 +51,57 @@
         "url": "https://github.com/sponsors/sindresorhus"
       }
     },
+    "node_modules/@asamuzakjp/css-color": {
+      "version": "5.1.11",
+      "resolved": "https://registry.npmjs.org/@asamuzakjp/css-color/-/css-color-5.1.11.tgz",
+      "integrity": "sha512-KVw6qIiCTUQhByfTd78h2yD1/00waTmm9uy/R7Ck/ctUyAPj+AEDLkQIdJW0T8+qGgj3j5bpNKK7Q3G+LedJWg==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@asamuzakjp/generational-cache": "^1.0.1",
+        "@csstools/css-calc": "^3.2.0",
+        "@csstools/css-color-parser": "^4.1.0",
+        "@csstools/css-parser-algorithms": "^4.0.0",
+        "@csstools/css-tokenizer": "^4.0.0"
+      },
+      "engines": {
+        "node": "^20.19.0 || ^22.12.0 || >=24.0.0"
+      }
+    },
+    "node_modules/@asamuzakjp/dom-selector": {
+      "version": "7.1.1",
+      "resolved": "https://registry.npmjs.org/@asamuzakjp/dom-selector/-/dom-selector-7.1.1.tgz",
+      "integrity": "sha512-67RZDnYRc8H/8MLDgQCDE//zoqVFwajkepHZgmXrbwybzXOEwOWGPYGmALYl9J2DOLfFPPs6kKCqmbzV895hTQ==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@asamuzakjp/generational-cache": "^1.0.1",
+        "@asamuzakjp/nwsapi": "^2.3.9",
+        "bidi-js": "^1.0.3",
+        "css-tree": "^3.2.1",
+        "is-potential-custom-element-name": "^1.0.1"
+      },
+      "engines": {
+        "node": "^20.19.0 || ^22.12.0 || >=24.0.0"
+      }
+    },
+    "node_modules/@asamuzakjp/generational-cache": {
+      "version": "1.0.1",
+      "resolved": "https://registry.npmjs.org/@asamuzakjp/generational-cache/-/generational-cache-1.0.1.tgz",
+      "integrity": "sha512-wajfB8KqzMCN2KGNFdLkReeHncd0AslUSrvHVvvYWuU8ghncRJoA50kT3zP9MVL0+9g4/67H+cdvBskj9THPzg==",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": "^20.19.0 || ^22.12.0 || >=24.0.0"
+      }
+    },
+    "node_modules/@asamuzakjp/nwsapi": {
+      "version": "2.3.9",
+      "resolved": "https://registry.npmjs.org/@asamuzakjp/nwsapi/-/nwsapi-2.3.9.tgz",
+      "integrity": "sha512-n8GuYSrI9bF7FFZ/SjhwevlHc8xaVlb/7HmHelnc/PZXBD2ZR49NnN9sMMuDdEGPeeRQ5d0hqlSlEpgCX3Wl0Q==",
+      "dev": true,
+      "license": "MIT"
+    },
     "node_modules/@babel/code-frame": {
       "version": "7.29.0",
       "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.29.0.tgz",
@@ -181,9 +245,9 @@
       }
     },
     "node_modules/@babel/helper-string-parser": {
-      "version": "7.27.1",
-      "resolved": "https://registry.npmjs.org/@babel/helper-string-parser/-/helper-string-parser-7.27.1.tgz",
-      "integrity": "sha512-qMlSxKbpRlAridDExk92nSobyDdpPijUq2DW6oDnUqd0iOGxmQjyqhMIihI9+zv4LPyZdRje2cavWPbCbWm3eA==",
+      "version": "7.29.7",
+      "resolved": "https://registry.npmjs.org/@babel/helper-string-parser/-/helper-string-parser-7.29.7.tgz",
+      "integrity": "sha512-Pb5ijPrZ89GDH8223L4UP8i6QApWxs04RbPQJTeWDV0/keR2E36MeKnyr6LYmUUvqRRI+Iv87SuF1W6ErINzYw==",
       "dev": true,
       "license": "MIT",
       "engines": {
@@ -191,9 +255,9 @@
       }
     },
     "node_modules/@babel/helper-validator-identifier": {
-      "version": "7.28.5",
-      "resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.28.5.tgz",
-      "integrity": "sha512-qSs4ifwzKJSV39ucNjsvc6WVHs6b7S03sOh2OcHF9UHfVPqWWALUsNUVzhSBiItjRZoLHx7nIarVjqKVusUZ1Q==",
+      "version": "7.29.7",
+      "resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.29.7.tgz",
+      "integrity": "sha512-qehxGkRj55h/ff8EMaJ+cYhyaKlHIxqYDn682wQD7RNp9UujOQsHog2uS0r2vzr4pW+sXf90NeeayjcNaX3fFg==",
       "dev": true,
       "license": "MIT",
       "engines": {
@@ -225,13 +289,13 @@
       }
     },
     "node_modules/@babel/parser": {
-      "version": "7.29.0",
-      "resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.29.0.tgz",
-      "integrity": "sha512-IyDgFV5GeDUVX4YdF/3CPULtVGSXXMLh1xVIgdCgxApktqnQV0r7/8Nqthg+8YLGaAtdyIlo2qIdZrbCv4+7ww==",
+      "version": "7.29.7",
+      "resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.29.7.tgz",
+      "integrity": "sha512-hnORnjP/1P/zFEndoeX+n+t1RwWRJiJpM/jO7FW32Kn9r5+sJB2JWOdYo4L6k78j15eCwY3Gm/7364B1EMwtNg==",
       "dev": true,
       "license": "MIT",
       "dependencies": {
-        "@babel/types": "^7.29.0"
+        "@babel/types": "^7.29.7"
       },
       "bin": {
         "parser": "bin/babel-parser.js"
@@ -272,6 +336,16 @@
         "@babel/core": "^7.0.0-0"
       }
     },
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+      "integrity": "sha512-3O9Tf67pGhgOv9jM35AbhkXAKi13f3oy3aE4CSgr+TckGeY+/iu97ZXN+J7DpHPzLbVApFd1IFhcnBjREYXYcg==",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=20.18.1"
+      }
+    },
     "node_modules/unified": {
       "version": "11.0.5",
       "resolved": "https://registry.npmjs.org/unified/-/unified-11.0.5.tgz",
@@ -4260,6 +5411,174 @@
         "url": "https://github.com/sponsors/jonschlinkert"
       }
     },
+    "node_modules/vitest": {
+      "version": "4.1.7",
+      "resolved": "https://registry.npmjs.org/vitest/-/vitest-4.1.7.tgz",
+      "integrity": "sha512-flYyaFd2CgoCoU+0UKt3pxksgC+S02iTDN0n3LtqaMeXsI9SBcdNujc2k0DeFLzUn/0k538yNjOSdwgCqcrwJA==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@vitest/expect": "4.1.7",
+        "@vitest/mocker": "4.1.7",
+        "@vitest/pretty-format": "4.1.7",
+        "@vitest/runner": "4.1.7",
+        "@vitest/snapshot": "4.1.7",
+        "@vitest/spy": "4.1.7",
+        "@vitest/utils": "4.1.7",
+        "es-module-lexer": "^2.0.0",
+        "expect-type": "^1.3.0",
+        "magic-string": "^0.30.21",
+        "obug": "^2.1.1",
+        "pathe": "^2.0.3",
+        "picomatch": "^4.0.3",
+        "std-env": "^4.0.0-rc.1",
+        "tinybench": "^2.9.0",
+        "tinyexec": "^1.0.2",
+        "tinyglobby": "^0.2.15",
+        "tinyrainbow": "^3.1.0",
+        "vite": "^6.0.0 || ^7.0.0 || ^8.0.0",
+        "why-is-node-running": "^2.3.0"
+      },
+      "bin": {
+        "vitest": "vitest.mjs"
+      },
+      "engines": {
+        "node": "^20.0.0 || ^22.0.0 || >=24.0.0"
+      },
+      "funding": {
+        "url": "https://opencollective.com/vitest"
+      },
+      "peerDependencies": {
+        "@edge-runtime/vm": "*",
+        "@opentelemetry/api": "^1.9.0",
+        "@types/node": "^20.0.0 || ^22.0.0 || >=24.0.0",
+        "@vitest/browser-playwright": "4.1.7",
+        "@vitest/browser-preview": "4.1.7",
+        "@vitest/browser-webdriverio": "4.1.7",
+        "@vitest/coverage-istanbul": "4.1.7",
+        "@vitest/coverage-v8": "4.1.7",
+        "@vitest/ui": "4.1.7",
+        "happy-dom": "*",
+        "jsdom": "*",
+        "vite": "^6.0.0 || ^7.0.0 || ^8.0.0"
+      },
+      "peerDependenciesMeta": {
+        "@edge-runtime/vm": {
+          "optional": true
+        },
+        "@opentelemetry/api": {
+          "optional": true
+        },
+        "@types/node": {
+          "optional": true
+        },
+        "@vitest/browser-playwright": {
+          "optional": true
+        },
+        "@vitest/browser-preview": {
+          "optional": true
+        },
+        "@vitest/browser-webdriverio": {
+          "optional": true
+        },
+        "@vitest/coverage-istanbul": {
+          "optional": true
+        },
+        "@vitest/coverage-v8": {
+          "optional": true
+        },
+        "@vitest/ui": {
+          "optional": true
+        },
+        "happy-dom": {
+          "optional": true
+        },
+        "jsdom": {
+          "optional": true
+        },
+        "vite": {
+          "optional": false
+        }
+      }
+    },
+    "node_modules/vitest/node_modules/picomatch": {
+      "version": "4.0.4",
+      "resolved": "https://registry.npmjs.org/picomatch/-/picomatch-4.0.4.tgz",
+      "integrity": "sha512-QP88BAKvMam/3NxH6vj2o21R6MjxZUAd6nlwAS/pnGvN9IVLocLHxGYIzFhg6fUQ+5th6P4dv4eW9jX3DSIj7A==",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=12"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/jonschlinkert"
+      }
+    },
+    "node_modules/w3c-xmlserializer": {
+      "version": "5.0.0",
+      "resolved": "https://registry.npmjs.org/w3c-xmlserializer/-/w3c-xmlserializer-5.0.0.tgz",
+      "integrity": "sha512-o8qghlI8NZHU1lLPrpi2+Uq7abh4GGPpYANlalzWxyWteJOCsr/P+oPBA49TOLu5FTZO4d3F9MnWJfiMo4BkmA==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "xml-name-validator": "^5.0.0"
+      },
+      "engines": {
+        "node": ">=18"
+      }
+    },
+    "node_modules/webidl-conversions": {
+      "version": "8.0.1",
+      "resolved": "https://registry.npmjs.org/webidl-conversions/-/webidl-conversions-8.0.1.tgz",
+      "integrity": "sha512-BMhLD/Sw+GbJC21C/UgyaZX41nPt8bUTg+jWyDeg7e7YN4xOM05YPSIXceACnXVtqyEw/LMClUQMtMZ+PGGpqQ==",
+      "dev": true,
+      "license": "BSD-2-Clause",
+      "engines": {
+        "node": ">=20"
+      }
+    },
+    "node_modules/whatwg-mimetype": {
+      "version": "5.0.0",
+      "resolved": "https://registry.npmjs.org/whatwg-mimetype/-/whatwg-mimetype-5.0.0.tgz",
+      "integrity": "sha512-sXcNcHOC51uPGF0P/D4NVtrkjSU2fNsm9iog4ZvZJsL3rjoDAzXZhkm2MWt1y+PUdggKAYVoMAIYcs78wJ51Cw==",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=20"
+      }
+    },
+    "node_modules/whatwg-url": {
+      "version": "16.0.1",
+      "resolved": "https://registry.npmjs.org/whatwg-url/-/whatwg-url-16.0.1.tgz",
+      "integrity": "sha512-1to4zXBxmXHV3IiSSEInrreIlu02vUOvrhxJJH5vcxYTBDAx51cqZiKdyTxlecdKNSjj8EcxGBxNf6Vg+945gw==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@exodus/bytes": "^1.11.0",
+        "tr46": "^6.0.0",
+        "webidl-conversions": "^8.0.1"
+      },
+      "engines": {
+        "node": "^20.19.0 || ^22.12.0 || >=24.0.0"
+      }
+    },
+    "node_modules/why-is-node-running": {
+      "version": "2.3.0",
+      "resolved": "https://registry.npmjs.org/why-is-node-running/-/why-is-node-running-2.3.0.tgz",
+      "integrity": "sha512-hUrmaWBdVDcxvYqnyh09zunKzROWjbZTiNy8dBEjkS7ehEDQibXJ7XvlmtbwuTclUiIyN+CyXQD4Vmko8fNm8w==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "siginfo": "^2.0.0",
+        "stackback": "0.0.2"
+      },
+      "bin": {
+        "why-is-node-running": "cli.js"
+      },
+      "engines": {
+        "node": ">=8"
+      }
+    },
     "node_modules/ws": {
       "version": "8.18.3",
       "resolved": "https://registry.npmjs.org/ws/-/ws-8.18.3.tgz",
@@ -4281,6 +5600,23 @@
         }
       }
     },
+    "node_modules/xml-name-validator": {
+      "version": "5.0.0",
+      "resolved": "https://registry.npmjs.org/xml-name-validator/-/xml-name-validator-5.0.0.tgz",
+      "integrity": "sha512-EvGK8EJ3DhaHfbRlETOWAS5pO9MZITeauHKJyb8wyajUfQUenkIg2MvLDTZ4T/TgIcm3HU0TFBgWWboAZ30UHg==",
+      "dev": true,
+      "license": "Apache-2.0",
+      "engines": {
+        "node": ">=18"
+      }
+    },
+    "node_modules/xmlchars": {
+      "version": "2.2.0",
+      "resolved": "https://registry.npmjs.org/xmlchars/-/xmlchars-2.2.0.tgz",
+      "integrity": "sha512-JZnDKK8B0RCDw84FNdDAIpZK+JuJw+s7Lz8nksI7SIuU3UXJJslUthsi+uWBUYOwPFwW7W7PRLRfUKpxjtjFCw==",
+      "dev": true,
+      "license": "MIT"
+    },
     "node_modules/xmlhttprequest-ssl": {
       "version": "2.1.2",
       "resolved": "https://registry.npmjs.org/xmlhttprequest-ssl/-/xmlhttprequest-ssl-2.1.2.tgz",
diff --git a/apps/finance-ai-agent-demo/frontend/package.json b/apps/finance-ai-agent-demo/frontend/package.json
index a75d4c48..ed846051 100644
--- a/apps/finance-ai-agent-demo/frontend/package.json
+++ b/apps/finance-ai-agent-demo/frontend/package.json
@@ -6,7 +6,10 @@
   "scripts": {
     "dev": "vite",
     "build": "vite build",
-    "preview": "vite preview"
+    "preview": "vite preview",
+    "test": "vitest run",
+    "test:watch": "vitest",
+    "test:coverage": "vitest run --coverage"
   },
   "dependencies": {
     "lucide-react": "^0.400.0",
@@ -17,12 +20,18 @@
     "socket.io-client": "^4.8.3"
   },
   "devDependencies": {
+    "@testing-library/jest-dom": "^6.9.1",
+    "@testing-library/react": "^16.3.2",
+    "@testing-library/user-event": "^14.6.1",
     "@types/react": "^18.3.3",
     "@types/react-dom": "^18.3.0",
     "@vitejs/plugin-react": "^4.3.1",
+    "@vitest/coverage-v8": "^4.1.7",
     "autoprefixer": "^10.4.19",
+    "jsdom": "^29.1.1",
     "postcss": "^8.4.39",
     "tailwindcss": "^3.4.6",
-    "vite": "^6.4.2"
+    "vite": "^6.4.2",
+    "vitest": "^4.1.7"
   }
 }
diff --git a/apps/finance-ai-agent-demo/frontend/src/test/ToolCallBubble.test.jsx b/apps/finance-ai-agent-demo/frontend/src/test/ToolCallBubble.test.jsx
new file mode 100644
index 00000000..84cc6d6f
--- /dev/null
+++ b/apps/finance-ai-agent-demo/frontend/src/test/ToolCallBubble.test.jsx
@@ -0,0 +1,178 @@
+/**
+ * Tests for ToolCallBubble rendering the suggest_portfolio_hedge tool call.
+ *
+ * Covers:
+ * - Running state (spinner, no output toggle)
+ * - Success state (tick, elapsed time, expandable output)
+ * - Error state (cross icon, output visible)
+ * - Output expand/collapse toggle
+ * - Pretty-printed JSON output for hedge results
+ * - Args rendered correctly in the header
+ */
+
+import { describe, it, expect } from "vitest";
+import { render, screen, fireEvent } from "@testing-library/react";
+import ToolCallBubble from "../components/ToolCallBubble";
+import { makeToolCall, makeRunningToolCall, makeErrorToolCall, hedgeOutput } from "./hedgeFixtures";
+
+// ---------------------------------------------------------------------------
+// Running state
+// ---------------------------------------------------------------------------
+
+describe("ToolCallBubble — running state", () => {
+  it("shows tool name and account_id arg in header", () => {
+    render(<ToolCallBubble toolCall={makeRunningToolCall()} />);
+    expect(screen.getByText(/suggest_portfolio_hedge/)).toBeInTheDocument();
+    expect(screen.getByText(/account_id="ACC-001"/)).toBeInTheDocument();
+  });
+
+  it("renders a spinner element (animate-spin class)", () => {
+    const { container } = render(<ToolCallBubble toolCall={makeRunningToolCall()} />);
+    expect(container.querySelector(".animate-spin")).toBeInTheDocument();
+  });
+
+  it("does not show elapsed time while running", () => {
+    render(<ToolCallBubble toolCall={makeRunningToolCall()} />);
+    expect(screen.queryByText(/ms/)).not.toBeInTheDocument();
+  });
+
+  it("does not show output toggle while running", () => {
+    render(<ToolCallBubble toolCall={makeRunningToolCall()} />);
+    expect(screen.queryByText(/output/i)).not.toBeInTheDocument();
+  });
+});
+
+// ---------------------------------------------------------------------------
+// Success state
+// ---------------------------------------------------------------------------
+
+describe("ToolCallBubble — success state", () => {
+  it("shows tool name in header", () => {
+    render(<ToolCallBubble toolCall={makeToolCall()} />);
+    expect(screen.getByText(/suggest_portfolio_hedge/)).toBeInTheDocument();
+  });
+
+  it("renders risk_focus arg in header", () => {
+    render(<ToolCallBubble toolCall={makeToolCall()} />);
+    expect(screen.getByText(/risk_focus="all"/)).toBeInTheDocument();
+  });
+
+  it("shows elapsed time", () => {
+    render(<ToolCallBubble toolCall={makeToolCall({ elapsed_ms: 142 })} />);
+    expect(screen.getByText(/142ms/)).toBeInTheDocument();
+  });
+
+  it("shows success checkmark (✓)", () => {
+    render(<ToolCallBubble toolCall={makeToolCall()} />);
+    // ✓ is rendered as &#10003; which is the Unicode CHECK MARK
+    expect(screen.getByText("✓")).toBeInTheDocument();
+  });
+
+  it("shows 'Show output' button when output is present", () => {
+    render(<ToolCallBubble toolCall={makeToolCall()} />);
+    expect(screen.getByText(/show output/i)).toBeInTheDocument();
+  });
+
+  it("output is collapsed by default", () => {
+    render(<ToolCallBubble toolCall={makeToolCall()} />);
+    expect(screen.queryByText(/hedge_recommendations/i)).not.toBeInTheDocument();
+  });
+});
+
+// ---------------------------------------------------------------------------
+// Output expand / collapse
+// ---------------------------------------------------------------------------
+
+describe("ToolCallBubble — expand/collapse output", () => {
+  it("expands output on 'Show output' click", () => {
+    const { container } = render(<ToolCallBubble toolCall={makeToolCall()} />);
+    fireEvent.click(screen.getByText(/show output/i));
+    // Pretty-printed JSON inside the <pre> block should contain hedge_recommendations
+    const pre = container.querySelector("pre");
+    expect(pre).toBeInTheDocument();
+    expect(pre.textContent).toContain("hedge_recommendations");
+  });
+
+  it("shows 'Hide output' after expanding", () => {
+    render(<ToolCallBubble toolCall={makeToolCall()} />);
+    fireEvent.click(screen.getByText(/show output/i));
+    expect(screen.getByText(/hide output/i)).toBeInTheDocument();
+  });
+
+  it("collapses output on second click", () => {
+    const { container } = render(<ToolCallBubble toolCall={makeToolCall()} />);
+    fireEvent.click(screen.getByText(/show output/i));
+    fireEvent.click(screen.getByText(/hide output/i));
+    // The <pre> block should be gone after collapsing
+    expect(container.querySelector("pre")).not.toBeInTheDocument();
+    expect(screen.getByText(/show output/i)).toBeInTheDocument();
+  });
+
+  it("pretty-prints hedge recommendation JSON when expanded", () => {
+    render(<ToolCallBubble toolCall={makeToolCall()} />);
+    fireEvent.click(screen.getByText(/show output/i));
+    expect(screen.getByText(/hedge_recommendations/)).toBeInTheDocument();
+    expect(screen.getByText(/risk_factors_identified/)).toBeInTheDocument();
+  });
+
+  it("shows disclaimer text when expanded", () => {
+    render(<ToolCallBubble toolCall={makeToolCall()} />);
+    fireEvent.click(screen.getByText(/show output/i));
+    expect(screen.getByText(/algorithmically/i)).toBeInTheDocument();
+  });
+});
+
+// ---------------------------------------------------------------------------
+// Error state
+// ---------------------------------------------------------------------------
+
+describe("ToolCallBubble — error state", () => {
+  it("shows error cross (✗) icon", () => {
+    render(<ToolCallBubble toolCall={makeErrorToolCall()} />);
+    expect(screen.getByText("✗")).toBeInTheDocument();
+  });
+
+  it("shows elapsed time on error", () => {
+    render(<ToolCallBubble toolCall={makeErrorToolCall({ elapsed_ms: 55 })} />);
+    expect(screen.getByText(/55ms/)).toBeInTheDocument();
+  });
+
+  it("shows error output when expanded", () => {
+    render(<ToolCallBubble toolCall={makeErrorToolCall()} />);
+    fireEvent.click(screen.getByText(/show output/i));
+    expect(screen.getByText(/Database connection failed/)).toBeInTheDocument();
+  });
+});
+
+// ---------------------------------------------------------------------------
+// Args rendering edge cases
+// ---------------------------------------------------------------------------
+
+describe("ToolCallBubble — args rendering", () => {
+  it("renders only account_id when risk_focus is omitted", () => {
+    const toolCall = makeToolCall({ args: { account_id: "ACC-007" } });
+    render(<ToolCallBubble toolCall={toolCall} />);
+    expect(screen.getByText(/account_id="ACC-007"/)).toBeInTheDocument();
+  });
+
+  it("renders both args when risk_focus is provided", () => {
+    const toolCall = makeToolCall({
+      args: { account_id: "ACC-003", risk_focus: "sector" },
+    });
+    render(<ToolCallBubble toolCall={toolCall} />);
+    expect(screen.getByText(/risk_focus="sector"/)).toBeInTheDocument();
+  });
+
+  it("handles empty args object gracefully", () => {
+    const toolCall = makeToolCall({ args: {} });
+    render(<ToolCallBubble toolCall={toolCall} />);
+    // Should render tool name with empty parens, no crash
+    expect(screen.getByText(/suggest_portfolio_hedge/)).toBeInTheDocument();
+  });
+
+  it("handles null args gracefully", () => {
+    const toolCall = makeToolCall({ args: null });
+    render(<ToolCallBubble toolCall={toolCall} />);
+    expect(screen.getByText(/suggest_portfolio_hedge/)).toBeInTheDocument();
+  });
+});
diff --git a/apps/finance-ai-agent-demo/frontend/src/test/chatReducer.test.js b/apps/finance-ai-agent-demo/frontend/src/test/chatReducer.test.js
new file mode 100644
index 00000000..2f0142d5
--- /dev/null
+++ b/apps/finance-ai-agent-demo/frontend/src/test/chatReducer.test.js
@@ -0,0 +1,345 @@
+/**
+ * Tests for the chatReducer handling suggest_portfolio_hedge tool call events.
+ *
+ * Exercises the ADD_TOOL_CALL_START → UPDATE_TOOL_CALL → AGENT_COMPLETE
+ * lifecycle that the ToolCallBubble ultimately renders.
+ */
+
+import { describe, it, expect } from "vitest";
+import { makeToolCall, makeRunningToolCall, hedgeOutput } from "./hedgeFixtures";
+
+// Import the reducer directly — it is not exported from useChat.js, so we
+// replicate just the relevant cases here to keep tests self-contained and fast.
+// If the reducer is ever extracted, these tests can import it directly.
+
+// ---------------------------------------------------------------------------
+// Inline reducer (mirrors useChat.js chatReducer exactly for the relevant cases)
+// ---------------------------------------------------------------------------
+
+function chatReducer(state, action) {
+  switch (action.type) {
+    case "ADD_TOOL_CALL_START":
+      return {
+        ...state,
+        toolCalls: [
+          ...state.toolCalls,
+          {
+            id: action.payload.tool_call_id,
+            name: action.payload.tool_name,
+            args: action.payload.tool_args,
+            status: "running",
+            output: null,
+            elapsed_ms: null,
+          },
+        ],
+      };
+
+    case "UPDATE_TOOL_CALL":
+      return {
+        ...state,
+        toolCalls: state.toolCalls.map((tc) =>
+          tc.id === action.payload.tool_call_id
+            ? {
+                ...tc,
+                status: action.payload.status,
+                output: action.payload.output,
+                elapsed_ms: action.payload.elapsed_ms,
+              }
+            : tc
+        ),
+      };
+
+    case "AGENT_COMPLETE": {
+      const streamingExists = state.messages.find((m) => m.id === action.payload.message_id);
+      if (streamingExists) {
+        return {
+          ...state,
+          messages: state.messages.map((m) =>
+            m.id === action.payload.message_id
+              ? {
+                  ...m,
+                  content: action.payload.response || m.content,
+                  isStreaming: false,
+                  toolCalls: [...state.toolCalls],
+                }
+              : m
+          ),
+          isLoading: false,
+          toolCalls: [],
+        };
+      }
+      return {
+        ...state,
+        messages: [
+          ...state.messages,
+          {
+            id: action.payload.message_id,
+            role: "assistant",
+            content: action.payload.response,
+            timestamp: new Date().toISOString(),
+            toolCalls: [...state.toolCalls],
+          },
+        ],
+        isLoading: false,
+        toolCalls: [],
+      };
+    }
+
+    default:
+      return state;
+  }
+}
+
+const emptyState = { messages: [], toolCalls: [], isLoading: true };
+
+// ---------------------------------------------------------------------------
+// ADD_TOOL_CALL_START
+// ---------------------------------------------------------------------------
+
+describe("chatReducer — ADD_TOOL_CALL_START for suggest_portfolio_hedge", () => {
+  const startPayload = {
+    tool_call_id: "tc-001",
+    tool_name: "suggest_portfolio_hedge",
+    tool_args: { account_id: "ACC-001", risk_focus: "all" },
+  };
+
+  it("adds tool call to toolCalls list", () => {
+    const state = chatReducer(emptyState, { type: "ADD_TOOL_CALL_START", payload: startPayload });
+    expect(state.toolCalls).toHaveLength(1);
+  });
+
+  it("sets correct tool name", () => {
+    const state = chatReducer(emptyState, { type: "ADD_TOOL_CALL_START", payload: startPayload });
+    expect(state.toolCalls[0].name).toBe("suggest_portfolio_hedge");
+  });
+
+  it("sets status to running", () => {
+    const state = chatReducer(emptyState, { type: "ADD_TOOL_CALL_START", payload: startPayload });
+    expect(state.toolCalls[0].status).toBe("running");
+  });
+
+  it("sets output and elapsed_ms to null initially", () => {
+    const state = chatReducer(emptyState, { type: "ADD_TOOL_CALL_START", payload: startPayload });
+    expect(state.toolCalls[0].output).toBeNull();
+    expect(state.toolCalls[0].elapsed_ms).toBeNull();
+  });
+
+  it("preserves args on the tool call", () => {
+    const state = chatReducer(emptyState, { type: "ADD_TOOL_CALL_START", payload: startPayload });
+    expect(state.toolCalls[0].args).toEqual({ account_id: "ACC-001", risk_focus: "all" });
+  });
+
+  it("does not mutate existing toolCalls", () => {
+    const existingCall = {
+      id: "tc-existing",
+      name: "get_account_details",
+      args: {},
+      status: "success",
+      output: "{}",
+      elapsed_ms: 50,
+    };
+    const stateWithExisting = { ...emptyState, toolCalls: [existingCall] };
+    const next = chatReducer(stateWithExisting, {
+      type: "ADD_TOOL_CALL_START",
+      payload: startPayload,
+    });
+    expect(next.toolCalls).toHaveLength(2);
+    expect(next.toolCalls[0]).toEqual(existingCall);
+  });
+});
+
+// ---------------------------------------------------------------------------
+// UPDATE_TOOL_CALL
+// ---------------------------------------------------------------------------
+
+describe("chatReducer — UPDATE_TOOL_CALL for suggest_portfolio_hedge", () => {
+  const stateWithRunning = chatReducer(emptyState, {
+    type: "ADD_TOOL_CALL_START",
+    payload: {
+      tool_call_id: "tc-001",
+      tool_name: "suggest_portfolio_hedge",
+      tool_args: { account_id: "ACC-001" },
+    },
+  });
+
+  const completePayload = {
+    tool_call_id: "tc-001",
+    status: "success",
+    output: JSON.stringify(hedgeOutput),
+    elapsed_ms: 142,
+  };
+
+  it("updates status to success", () => {
+    const state = chatReducer(stateWithRunning, {
+      type: "UPDATE_TOOL_CALL",
+      payload: completePayload,
+    });
+    expect(state.toolCalls[0].status).toBe("success");
+  });
+
+  it("sets output on the correct tool call", () => {
+    const state = chatReducer(stateWithRunning, {
+      type: "UPDATE_TOOL_CALL",
+      payload: completePayload,
+    });
+    const output = JSON.parse(state.toolCalls[0].output);
+    expect(output.account_id).toBe("ACC-001");
+    expect(output.hedge_recommendations).toBeInstanceOf(Array);
+  });
+
+  it("sets elapsed_ms", () => {
+    const state = chatReducer(stateWithRunning, {
+      type: "UPDATE_TOOL_CALL",
+      payload: completePayload,
+    });
+    expect(state.toolCalls[0].elapsed_ms).toBe(142);
+  });
+
+  it("does not affect other tool calls", () => {
+    const stateTwo = chatReducer(stateWithRunning, {
+      type: "ADD_TOOL_CALL_START",
+      payload: { tool_call_id: "tc-002", tool_name: "get_account_details", tool_args: {} },
+    });
+    const updated = chatReducer(stateTwo, { type: "UPDATE_TOOL_CALL", payload: completePayload });
+    expect(updated.toolCalls[1].status).toBe("running"); // tc-002 unchanged
+  });
+
+  it("handles error status correctly", () => {
+    const errorPayload = {
+      tool_call_id: "tc-001",
+      status: "error",
+      output: "DB error",
+      elapsed_ms: 10,
+    };
+    const state = chatReducer(stateWithRunning, {
+      type: "UPDATE_TOOL_CALL",
+      payload: errorPayload,
+    });
+    expect(state.toolCalls[0].status).toBe("error");
+    expect(state.toolCalls[0].output).toBe("DB error");
+  });
+});
+
+// ---------------------------------------------------------------------------
+// AGENT_COMPLETE — tool calls attached to assistant message
+// ---------------------------------------------------------------------------
+
+describe("chatReducer — AGENT_COMPLETE attaches hedge tool calls to message", () => {
+  // Build state: start hedge tool call, complete it, then agent_complete
+  let state = emptyState;
+  state = chatReducer(state, {
+    type: "ADD_TOOL_CALL_START",
+    payload: {
+      tool_call_id: "tc-001",
+      tool_name: "suggest_portfolio_hedge",
+      tool_args: { account_id: "ACC-001" },
+    },
+  });
+  state = chatReducer(state, {
+    type: "UPDATE_TOOL_CALL",
+    payload: {
+      tool_call_id: "tc-001",
+      status: "success",
+      output: JSON.stringify(hedgeOutput),
+      elapsed_ms: 142,
+    },
+  });
+
+  const completeAction = {
+    type: "AGENT_COMPLETE",
+    payload: {
+      message_id: "msg-001",
+      response: "Here are hedge recommendations for ACC-001...",
+      query_summary: null,
+    },
+  };
+
+  it("clears toolCalls from live state after agent_complete", () => {
+    const next = chatReducer(state, completeAction);
+    expect(next.toolCalls).toHaveLength(0);
+  });
+
+  it("attaches tool calls to the new assistant message", () => {
+    const next = chatReducer(state, completeAction);
+    const assistantMsg = next.messages.find((m) => m.role === "assistant");
+    expect(assistantMsg).toBeDefined();
+    expect(assistantMsg.toolCalls).toHaveLength(1);
+    expect(assistantMsg.toolCalls[0].name).toBe("suggest_portfolio_hedge");
+  });
+
+  it("assistant message contains hedge output in its tool call", () => {
+    const next = chatReducer(state, completeAction);
+    const assistantMsg = next.messages.find((m) => m.role === "assistant");
+    const output = JSON.parse(assistantMsg.toolCalls[0].output);
+    expect(output.hedge_recommendations.length).toBeGreaterThan(0);
+  });
+
+  it("sets isLoading to false", () => {
+    const next = chatReducer(state, completeAction);
+    expect(next.isLoading).toBe(false);
+  });
+
+  it("agent_complete on a streaming message updates it in-place", () => {
+    // Simulate a streaming message already existing
+    const streamingState = {
+      ...state,
+      messages: [
+        {
+          id: "msg-001",
+          role: "assistant",
+          content: "partial...",
+          isStreaming: true,
+          toolCalls: [],
+        },
+      ],
+    };
+    const next = chatReducer(streamingState, completeAction);
+    const assistantMsg = next.messages.find((m) => m.id === "msg-001");
+    expect(assistantMsg.isStreaming).toBe(false);
+    expect(assistantMsg.content).toBe("Here are hedge recommendations for ACC-001...");
+  });
+});
+
+// ---------------------------------------------------------------------------
+// Full lifecycle simulation
+// ---------------------------------------------------------------------------
+
+describe("chatReducer — full suggest_portfolio_hedge lifecycle", () => {
+  it("running → success → attached to message without errors", () => {
+    let s = emptyState;
+
+    // 1. Tool call starts
+    s = chatReducer(s, {
+      type: "ADD_TOOL_CALL_START",
+      payload: {
+        tool_call_id: "tc-hedge",
+        tool_name: "suggest_portfolio_hedge",
+        tool_args: { account_id: "ACC-005", risk_focus: "sector" },
+      },
+    });
+    expect(s.toolCalls[0].status).toBe("running");
+
+    // 2. Tool call completes
+    s = chatReducer(s, {
+      type: "UPDATE_TOOL_CALL",
+      payload: {
+        tool_call_id: "tc-hedge",
+        status: "success",
+        output: JSON.stringify(hedgeOutput),
+        elapsed_ms: 200,
+      },
+    });
+    expect(s.toolCalls[0].status).toBe("success");
+
+    // 3. Agent completes
+    s = chatReducer(s, {
+      type: "AGENT_COMPLETE",
+      payload: { message_id: "msg-final", response: "Done.", query_summary: null },
+    });
+    expect(s.toolCalls).toHaveLength(0);
+
+    const msg = s.messages.find((m) => m.id === "msg-final");
+    expect(msg.toolCalls[0].name).toBe("suggest_portfolio_hedge");
+    expect(msg.toolCalls[0].elapsed_ms).toBe(200);
+  });
+});
diff --git a/apps/finance-ai-agent-demo/frontend/src/test/hedgeFixtures.js b/apps/finance-ai-agent-demo/frontend/src/test/hedgeFixtures.js
new file mode 100644
index 00000000..4995d793
--- /dev/null
+++ b/apps/finance-ai-agent-demo/frontend/src/test/hedgeFixtures.js
@@ -0,0 +1,97 @@
+/**
+ * Shared test fixtures for suggest_portfolio_hedge frontend tests.
+ */
+
+export const hedgeOutput = {
+  account_id: "ACC-001",
+  risk_profile: "aggressive",
+  esg_mandate: false,
+  risk_focus: "all",
+  portfolio_summary: {
+    total_holdings: 6,
+    high_risk_positions: 2,
+    sector_breakdown: [
+      { sector: "Technology", pct: 40.0 },
+      { sector: "Energy", pct: 20.0 },
+    ],
+    region_breakdown: [
+      { region: "North America", pct: 65.0 },
+      { region: "Europe", pct: 20.0 },
+    ],
+    asset_class_breakdown: [
+      { asset_class: "Equity", pct: 80.0 },
+      { asset_class: "Bond", pct: 20.0 },
+    ],
+  },
+  risk_factors_identified: [
+    "High equity concentration: 80.0% of portfolio is in equities.",
+    "2 high-risk positions (risk_rating ≥ 7) totalling 20.0% of portfolio.",
+    "Sector concentration: Technology represents 40.0% of portfolio.",
+    "Regional concentration: North America represents 65.0% of portfolio.",
+  ],
+  hedge_recommendations: [
+    {
+      ticker: "SH",
+      name: "ProShares Short S&P500 ETF",
+      type: "Inverse ETF",
+      rationale: "Broad market hedge; gains when S&P 500 declines.",
+      risk_level: "medium",
+      hedge_dimension: "market",
+      trigger: "equity_pct=80.0%",
+    },
+    {
+      ticker: "GLD",
+      name: "SPDR Gold Shares",
+      type: "Safe Haven",
+      rationale: "Gold allocation offsets tail risk from 2 high-rated positions.",
+      risk_level: "low",
+      hedge_dimension: "market",
+      trigger: "high_risk_positions=2",
+    },
+    {
+      ticker: "PUT",
+      name: "Put options on QQQ",
+      type: "Options Strategy",
+      rationale: "Buy QQQ put options as targeted downside protection for tech-heavy portfolios.",
+      risk_level: "medium",
+      hedge_dimension: "sector",
+      trigger: "Technology=40.0%",
+    },
+    {
+      ticker: "EFA",
+      name: "iShares MSCI EAFE ETF",
+      type: "Geographic Diversification",
+      rationale: "Developed-market international exposure offsets US-heavy concentration.",
+      risk_level: "low",
+      hedge_dimension: "regional",
+      trigger: "North America=65.0%",
+    },
+  ],
+  disclaimer:
+    "These recommendations are generated algorithmically for illustrative purposes only. " +
+    "All hedging decisions should be reviewed by a qualified financial advisor.",
+};
+
+export function makeToolCall({
+  id = "tc-hedge-001",
+  name = "suggest_portfolio_hedge",
+  args = { account_id: "ACC-001", risk_focus: "all" },
+  status = "success",
+  output = JSON.stringify(hedgeOutput),
+  elapsed_ms = 142,
+} = {}) {
+  return { id, name, args, status, output, elapsed_ms };
+}
+
+export function makeRunningToolCall(overrides = {}) {
+  return makeToolCall({ status: "running", output: null, elapsed_ms: null, ...overrides });
+}
+
+export function makeErrorToolCall(overrides = {}) {
+  return makeToolCall({
+    status: "error",
+    output: "Database connection failed",
+    elapsed_ms: 55,
+    ...overrides,
+  });
+}
diff --git a/apps/finance-ai-agent-demo/frontend/src/test/setup.js b/apps/finance-ai-agent-demo/frontend/src/test/setup.js
new file mode 100644
index 00000000..d0de870d
--- /dev/null
+++ b/apps/finance-ai-agent-demo/frontend/src/test/setup.js
@@ -0,0 +1 @@
+import "@testing-library/jest-dom";
diff --git a/apps/finance-ai-agent-demo/frontend/vite.config.js b/apps/finance-ai-agent-demo/frontend/vite.config.js
index 94c0fa01..212e5277 100644
--- a/apps/finance-ai-agent-demo/frontend/vite.config.js
+++ b/apps/finance-ai-agent-demo/frontend/vite.config.js
@@ -3,6 +3,15 @@ import react from "@vitejs/plugin-react";
 
 export default defineConfig({
   plugins: [react()],
+  test: {
+    environment: "jsdom",
+    globals: true,
+    setupFiles: "./src/test/setup.js",
+    coverage: {
+      reporter: ["text", "lcov"],
+      include: ["src/components/**", "src/hooks/**"],
+    },
+  },
   server: {
     port: 3000,
     proxy: {