FinTurb Analytics

{
  "id": "aix_d25a1e6d3e",
  "name": "FinTurb Analytics",
  "operator": "(unclaimed - source: pulsemcp · publisher: github.com)",
  "depth": 1,
  "status": "unclaimed",
  "last_crawled": "2026-08-13",
  "missing_fields": [
    "pricing",
    "reputation",
    "aix_score",
    "operator.identity"
  ],
  "skills": [
    "general-tools"
  ],
  "protocols": {
    "mcp": "https://mcp-mkic.pythonanywhere.com/mcp",
    "a2a": null
  },
  "pricing": null,
  "regions": [
    "global"
  ],
  "languages": [
    "en"
  ],
  "reputation": null,
  "aix_score": null,
  "verification": {
    "identity": "none",
    "health": "liveness-only",
    "pricing": "unknown",
    "last_check": "2026-08-13T06:01:13.536Z"
  },
  "pricing_model": "unknown",
  "links": [
    {
      "label": "homepage",
      "url": "https://www.pulsemcp.com/servers/ai-intellicore-finturb"
    },
    {
      "label": "repository",
      "url": "https://github.com/ai-intellicore/finturb-mcp"
    },
    {
      "label": "listing",
      "url": "https://www.finturb.com/"
    }
  ],
  "avatar": "https://github.com/ai-intellicore.png?size=160",
  "socials": [
    {
      "label": "github",
      "url": "https://github.com/ai-intellicore"
    }
  ],
  "public_stats": {
    "gh_stars": 2
  },
  "unreachable": false,
  "profile": {
    "mcp_server": "FinTurb Analytics",
    "mcp_version": "1.27.0",
    "tool_count": 70,
    "tools": [
      {
        "name": "get_risk_score",
        "description": "Today's plain-English read on overall market risk and what regime markets are in.\n\n    Returns:\n      - **Signal Strategist composite** — the canonical headline figure:\n        composite_strategist (0-100), regime_strategist (Normal / Elevated /\n        Crisis), quadrant_strategist (Constructive / Trending / Stress /\n        Systemic Risk), gate_strategist (Fragility Gate active or dormant),\n        turb_pct (Financial Turbulence percentile), frag_pct (Financial\n        Fragility percentile). Calibrated on full 2008+ history. Lead the\n        narrative with these figures.\n      - **Legacy 3-way composite Risk Score** (0–100) and 4-tier Investment\n        Regime label (normal / elevated / stress / crisis). Kept for parallel\n        comparison during the parallel evaluation period; will be retired afterwards.\n      - Liquidity-adjusted Risk Score (the 4-way score) and its own regime\n        label, plus a decomposition (base score + funding-conditions boost +\n        fragility-meets-tight-liquidity kicker)\n      - Financial Fragility (Absorption Ratio, AR) percentile — systemic\n        coupling between asset classes\n      - Financial Turbulence (Mahalanobis Distance, MD) percentile — how\n        unusual today's cross-asset price moves are\n      - GDELT media tone (global news sentiment z-score)\n      - Joint stress flags including fragile-shock and the 4-way joint\n        signals (fragility × tight liquidity, tight Private Sector\n        Liquidity, tight Policy Liquidity Index)\n      - Global Liquidity Index, Policy Liquidity Index, Private Sector\n        Liquidity, Cross-Border Flows Index sub-block\n\n    Call this when the user asks about: \"how risky are markets right now\",\n    \"today's market regime\", \"should I be worried about a sell-off\",\n    \"are we in risk-on or risk-off\", \"what's the overall risk picture\",\n    \"is the market in stress\", \"what is the current regime\", or anything\n    asking for a single headline read on present-day market conditions.\n\n    Updated daily ~03:40 UTC. Do NOT use for historical trends — use\n    `get_risk_history` instead. Chain with `get_signal_strategist` for the\n    fuller dashboard-grade read.\n    "
      },
      {
        "name": "get_strategist_composite",
        "description": "Signal Strategist composite — the canonical headline read on today's\n    market regime, with no legacy fields in the response.\n\n    Returns:\n      - composite_strategist (0-100) — Turbulence-anchored composite\n        (0.6 × Financial Turbulence pct + 0.4 × Financial Fragility pct,\n        +5 bonus when both signals are in their top quartile, capped at 100)\n      - regime_strategist — Normal (<25), Elevated (25-75), or Crisis (>75)\n      - quadrant_strategist — Constructive / Trending / Stress / Systemic Risk\n      - gate_strategist — boolean (1/0); 1 means the Fragility Gate is active\n      - turb_pct, frag_pct — underlying signal percentiles\n      - data_as_of — date the snapshot was calibrated through\n\n    Call this when the user wants the Signal Strategist read without\n    the legacy 3-way / 4-way comparison clutter — for example: \"what's\n    today's Signal Strategist composite\", \"current quadrant\", \"is the\n    Fragility Gate active\". For the parallel comparison against the legacy composites,\n    use `get_risk_score` instead. Updated daily.\n\n    Updated daily ~03:53 UTC by build_risk_synthesizer.py.\n    "
      },
      {
        "name": "get_quadrant_state",
        "description": "Regime Quadrant — joint position of Financial Turbulence and\n    Financial Fragility. Useful when the user is specifically asking about\n    the four-archetype regime grid (Constructive / Trending / Stress /\n    Systemic Risk) rather than the headline composite score.\n\n    Returns:\n      - quadrant — current quadrant label\n      - turb_pct, frag_pct — coordinates inside the grid\n      - description — one-line plain-English read of the quadrant's meaning\n      - is_corner_cell — True if turbulence AND fragility are BOTH in their\n        top quartile (Systemic Risk corner; historically a 3.4× tail-risk\n        amplifier)\n\n    Call this when the user asks: \"what quadrant are we in\", \"is the\n    Systemic Risk corner active\", \"how concentrated is the market right\n    now\", or anything explicitly about the four-quadrant regime grid.\n\n    Updated daily ~03:53 UTC.\n    "
      },
      {
        "name": "get_risk_history",
        "description": "How market risk and the Investment Regime have evolved over the recent past.\n\n    Returns:\n      - **Signal Strategist read for today** (headline overlay) —\n        composite_strategist (0-100), regime_strategist (Normal /\n        Elevated / Crisis), quadrant_strategist (Constructive / Trending\n        / Stress / Systemic Risk), gate_strategist (Fragility Gate active\n        or dormant). Lead the narrative with these figures.\n      - **Legacy 4-tier daily history** — daily 3-way composite Risk Score\n        (0-100) for the last N days (default 90) with regime labels on\n        the retiring 4-tier ladder (normal / elevated / stress / crisis)\n        and a regime-duration counter. Kept for the parallel evaluation\n        period; the legacy daily label can diverge from today's strategist\n        read when the regime is shifting.\n\n    Call this when the user asks: \"how has risk changed over the last\n    month\", \"compared to last week\", \"is the regime getting worse\",\n    \"show me the trend\", \"how long have we been in stress\", \"regime\n    history\", \"track the risk over time\", \"did things improve since\n    last week\".\n\n    Strategist historical regime values are not yet persisted at this\n    endpoint — only today's strategist read is overlaid. For a single-day\n    point-in-time read use `get_risk_score` or `get_strategist_composite`.\n    "
      },
      {
        "name": "get_conditional_returns",
        "description": "How major asset classes have historically performed in each Investment Regime.\n\n    Returns:\n      - Mean forward return, probability of a negative return, and CVaR\n        (Conditional Value-at-Risk — the average loss in the worst 5% of\n        outcomes) for each core asset (SPY, HYG, EMB, GSG, GLD, VNQ, ACWX)\n        bucketed by Investment Regime\n      - Horizon parameter: '5d' (one trading week) or '21d' (one trading\n        month)\n\n    Call this when the user asks: \"what usually happens to stocks in a\n    stress regime\", \"what's the expected loss if we're in crisis\",\n    \"how does gold do in risk-off\", \"what's the historical drawdown\n    for high yield in elevated regime\", \"should I expect SPY to drop\",\n    \"what's the worst-case in this regime\".\n\n    Pair with `get_risk_score` so the user knows the current Investment\n    Regime before reading the conditional table.\n    "
      },
      {
        "name": "get_interaction_table",
        "description": "How an asset has performed historically when Fragility, Turbulence, and Sentiment all line up (or don't).\n\n    Returns:\n      - 2×2×2 historical conditional return table for one asset, broken\n        down by Financial Fragility (Absorption Ratio, AR) high/low,\n        Financial Turbulence (Mahalanobis Distance, MD) high/low, and\n        GDELT media tone positive/negative\n      - Available assets: SPY, BTC_USD, GLD, HYG, or 'all' for the\n        aggregate cross-asset table\n\n    Call this when the user asks: \"how does SPY do when everything is\n    bad at once\", \"what happens to gold when systemic risk and\n    turbulence both spike\", \"show me the joint conditioning\",\n    \"compound conditioning table\", \"all signals lining up scenario\",\n    or wants to drill into one asset's behaviour across the full\n    eight-cell stress map.\n\n    For single-signal regime-conditioned tables use\n    `get_conditional_returns`.\n    "
      },
      {
        "name": "get_turbulence_score",
        "description": "How unusual today's cross-asset price moves are versus their historical pattern.\n\n    Returns:\n      - Financial Turbulence (Mahalanobis Distance, MD) daily reading:\n        raw value, expanding-history percentile, quartile (1–4), and\n        regime label (Risk-On / Neutral / Financial Turbulence)\n      - 10-day rolling Financial Turbulence reading on the same scale —\n        smooths out single-day noise\n      - Master daily and 10-day percentiles across the unweighted\n        13-asset model\n\n    Call this when the user asks: \"how turbulent are markets\",\n    \"are today's moves unusual\", \"is there cross-asset stress\",\n    \"what is the turbulence reading\", \"how volatile is the market\",\n    \"is volatility elevated\", \"how big are today's market moves\n    historically\", \"is this a normal day or a statistically odd one\".\n\n    Pair with `get_signal_dates` for historical analogues, and with\n    `get_absorption_ratio` to separate \"today is unusual\" from\n    \"today is unusual AND the system is fragile\".\n    "
      },
      {
        "name": "get_transition_probabilities",
        "description": "The base-rate odds of staying in or moving out of today's Financial Turbulence state.\n\n    Returns:\n      - Markov transition matrices for the Financial Turbulence (Mahalanobis\n        Distance, MD) regime — both the daily reading and the smoother\n        10-day rolling reading\n      - For each turbulence state and how long it has lasted, the\n        probability of remaining versus transitioning to each other state\n      - A note that probabilities within ±3 percentage points of each\n        other are statistically indistinguishable\n\n    Call this when the user asks: \"how long does this regime last\",\n    \"what are the odds we stay in stress\", \"what's the base-rate path\n    from here\", \"probability we move out of risk-off\", \"is this turbulence\n    likely to persist\", \"how sticky is the current market state\".\n\n    Pair with `get_turbulence_score` so the user knows which state today\n    sits in before reading the transition odds.\n    "
      },
      {
        "name": "get_signal_dates",
        "description": "Historical episodes when Financial Turbulence flagged a bullish or bearish setup, and what happened next.\n\n    Returns:\n      - Type-A bearish (risk-off) signal dates: when Financial Turbulence\n        (Mahalanobis Distance, MD) flagged a likely sell-off setup, with\n        the percentile reading, signal strength, what asset prices did\n        afterwards, and whether the call worked out\n      - Type-B bullish (risk-on) signal dates with the same fields\n      - signal_type parameter: 'A', 'B', or 'both'\n\n    Call this when the user asks: \"what happened the last time markets\n    looked like this\", \"show me historical analogues\", \"hit rate of the\n    bearish signal\", \"did the bullish signal work in the past\",\n    \"track record of the turbulence signal\", \"case studies of past\n    risk-off episodes\".\n\n    Pair with `get_turbulence_score` so the user can compare today's\n    reading against the historical setups returned here.\n    "
      },
      {
        "name": "get_absorption_ratio",
        "description": "How tightly today's asset classes are moving together — a measure of Financial Fragility.\n\n    Returns Financial Fragility (Absorption Ratio, AR) — the share of\n    cross-asset return variance explained by the top two principal\n    components, i.e. how much of the market is being driven by a single\n    dominant factor. High values mean diversification is breaking down\n    and a shock in one asset spills into the rest of the system.\n\n    Returns:\n      - Three-tier Financial Fragility alert read across independent\n        rolling windows:\n          • 30-day Watch (Absorption Ratio above the 75th percentile)\n          • 60-day Warning (above the 90th percentile)\n          • 90-day Crisis (above the 95th percentile)\n      - Per tier: the raw Absorption Ratio level, its percentile rank,\n        whether the tier is currently triggered, and the threshold\n      - Overall alert level (none / watch / warning / crisis), number of\n        active tiers, and a plain-English coupling classification (Low /\n        Below Average / Above Average / High)\n\n    Call this when the user asks: \"is the market crowded\", \"are asset\n    classes moving together\", \"is diversification working\", \"is there\n    contagion risk\", \"systemic risk\", \"are we in a fragile market\",\n    \"PCA stress\", \"Absorption Ratio\", \"asset correlation breakdown\",\n    \"how coupled are markets right now\".\n\n    Updated daily ~00:30 UTC. For per-asset PC1/PC2 eigenvector loadings\n    across the three windows use `get_pc_loadings_history`. For the raw\n    AR time-series tail only use `get_fragility_loadings`.\n    "
      },
      {
        "name": "get_fragility_loadings",
        "description": "The raw 30-day history of Financial Fragility for charting or follow-on computation.\n\n    Returns:\n      - 30-day tail of the Financial Fragility (Absorption Ratio, AR)\n        time series — daily values plus their percentile rank and\n        coupling classification\n\n    Call this when the user asks: \"give me the raw Absorption Ratio\n    series\", \"fragility time series\", \"AR history\", \"I want to chart\n    the Absorption Ratio\", \"show the values not just the alert level\".\n\n    For the headline 3-tier alert read use `get_absorption_ratio`. For\n    per-asset PC1/PC2 eigenvector loadings broken down across\n    30/60/90-day windows use `get_pc_loadings_history` — that tool\n    returns the full eigenvector breakdown by asset and window.\n    "
      },
      {
        "name": "get_pc_loadings_history",
        "description": "Which specific assets are driving the dominant factors behind today's Financial Fragility.\n\n    Returns:\n      - Per-date variance shares for the first four principal components\n        (PC1–PC4) plus Financial Fragility (Absorption Ratio, AR =\n        PC1 + PC2)\n      - Per-date PC1 and PC2 eigenvector loading dictionaries keyed by\n        each of the 13 ETFs in the universe (ACWX, BWX, EMB, GLD, GSG,\n        HYG, LQD, MBB, MUB, SPTI, SPY, TIP, VNQ) — these tell you the\n        weight each asset contributes to the dominant risk factor on\n        each day\n      - Window parameter: 30, 60, or 90 day rolling PCA. Default 30.\n      - Days parameter: trailing observations to return, clamped to 1–90.\n        Default 60.\n\n    Call this when the user asks: \"which assets are driving systemic\n    coupling\", \"which assets are dominating the market right now\",\n    \"is this a credit-led or equity-led stress episode\", \"how has the\n    factor composition shifted\", \"what's inside PC1 today\", \"show me\n    the eigenvector loadings\", \"decompose the Absorption Ratio by\n    asset\".\n\n    Per-date loadings are sign-aligned against the full-period reference so\n    directions are comparable across history. Sum-of-squares of each\n    eigenvector equals 1 by construction.\n\n    Updated daily ~00:35 UTC. For the aggregate 3-tier alert read use\n    `get_absorption_ratio`; for the raw Absorption Ratio time series\n    only use `get_fragility_loadings`.\n    "
      },
      {
        "name": "get_media_sentiment",
        "description": "How the global news cycle is talking about specific assets right now.\n\n    Returns:\n      - Per-ticker GDELT media tone (global news sentiment) and news\n        volume — both as raw values and as z-scores versus their own\n        history (positive z-score means more upbeat than usual, negative\n        means more negative than usual)\n      - Composite sentiment signal blending tone and volume\n      - Tone momentum and any active alerts\n      - Coverage across 27+ assets; pass a comma-separated list of\n        tickers, or omit for the full universe\n\n    Call this when the user asks: \"what's the news saying about SPY\",\n    \"media sentiment on gold\", \"is the news positive or negative on\n    bitcoin\", \"how is the press treating high yield\", \"GDELT tone for\n    EMB\", \"narrative on this asset\", \"news sentiment\".\n\n    Updated daily ~03:25 UTC. For a ranked heatmap of all assets use\n    `get_sentiment_heatmap`; for outliers only use `get_sentiment_alerts`.\n    "
      },
      {
        "name": "get_sentiment_heatmap",
        "description": "Which assets the news cycle is talking about most loudly today, ranked.\n\n    Returns:\n      - Every tracked asset sorted by the magnitude of its composite\n        GDELT media tone signal (positive or negative — what matters\n        for the ranking is how far from neutral it is)\n      - Per-asset tone, volume, z-scores, composite signal, and any\n        active alerts\n\n    Call this when the user asks: \"what assets is the news focused on\",\n    \"rank assets by sentiment intensity\", \"show me the sentiment\n    heatmap\", \"which tickers are getting the most attention\", \"where\n    is the narrative loudest\", \"media tone leaderboard\".\n\n    For a single-ticker drill-down use `get_media_sentiment`; for the\n    short-list of statistical outliers only use `get_sentiment_alerts`.\n    "
      },
      {
        "name": "get_sentiment_alerts",
        "description": "The short-list of assets where today's news sentiment is genuinely unusual.\n\n    Returns:\n      - Every asset whose GDELT media tone z-score or news volume\n        z-score is more than two standard deviations from its own\n        history (|z| > 2.0) — i.e. a statistically meaningful sentiment\n        or attention spike, not just a tilt\n      - Per-asset tone, volume, composite signal, and z-scores so the\n        user can see exactly how unusual each anomaly is\n\n    Call this when the user asks: \"what's unusual in the news today\",\n    \"any sentiment anomalies\", \"which assets have spiked in news\n    coverage\", \"outliers in media tone\", \"is anything off-trend in\n    sentiment\", \"actionable sentiment short-list\".\n\n    For a single-ticker drill-down use `get_media_sentiment`; for the\n    full ranked heatmap use `get_sentiment_heatmap`.\n    "
      },
      {
        "name": "get_geopolitical_tone",
        "description": "How tense the world looks today through the lens of global event coverage.\n\n    Returns:\n      - Average Goldstein Scale score — a -10 to +10 conflict-vs-cooperation\n        index across all events captured in GDELT. More negative = more\n        conflict-heavy global news flow\n      - Average conflict ratio — the share of events classified as material\n        conflict\n      - Average event-level tone across the GDELT full dataset\n      - Number of asset coverage rows feeding the snapshot\n\n    Call this when the user asks: \"how geopolitically tense is the\n    world right now\", \"are conflicts escalating\", \"what's the\n    geopolitical risk read\", \"is there war risk in the news\",\n    \"cross-border tension\", \"Goldstein Scale\", \"macro geopolitical\n    backdrop\".\n\n    For per-asset GDELT media tone use `get_media_sentiment` or\n    `get_sentiment_alerts`; this tool is the global geopolitical\n    backdrop, not asset-specific.\n    "
      },
      {
        "name": "get_global_liquidity",
        "description": "How easy or hard it is to borrow money around the world right now, plus the central-bank stance behind it.\n\n    Returns:\n      - Global Liquidity Index (GLI), 0–100 — the headline composite of\n        global funding conditions. Below 50 means tightening, above 50\n        means easing\n      - Policy Liquidity Index (PLI) — the central-bank stance\n        sub-component (balance sheets, policy rates)\n      - Private Sector Liquidity (PSI) — dealer balance sheets and\n        private credit conditions\n      - Cross-Border Flows Index (XFI) — international banking and\n        capital movements; may be a bridge-model nowcast for the most\n        recent months (`xfi_is_nowcast` tells you which)\n      - Cycle phase classification (Calm / Speculation / Turbulence /\n        Rebound)\n      - Regional breakdown across the major economies\n\n    Call this when the user asks: \"how is global liquidity\", \"is it\n    easy to borrow right now\", \"borrowing conditions\", \"funding\n    conditions\", \"credit conditions\", \"dollar liquidity\", \"central\n    bank policy stance\", \"QT\", \"quantitative tightening\", \"are\n    central banks easing or tightening\", \"cross-border capital\n    flows\", \"is the system flush with cash\".\n\n    Pre-computed daily ~03:00 UTC from BIS / FRED / ECB primary sources;\n    strictly read-only. For monthly history use `get_liquidity_history`;\n    for region-by-region detail use `get_regional_liquidity`.\n    "
      },
      {
        "name": "get_liquidity_history",
        "description": "How borrowing and funding conditions have evolved over the recent past, month by month.\n\n    Returns:\n      - Monthly time series of the Global Liquidity Index (GLI) and its\n        sub-components — Policy Liquidity Index (PLI, central-bank\n        stance), Private Sector Liquidity (PSI, dealer and private\n        credit), and Cross-Border Flows Index (XFI, international\n        capital movements)\n      - Cycle phase classification for each observation (Calm /\n        Speculation / Turbulence / Rebound)\n      - months parameter: default 12, clamped to 1–240\n\n    Call this when the user asks: \"how has liquidity changed over the\n    last year\", \"trend in funding conditions\", \"have central banks\n    been easing or tightening recently\", \"QT history\", \"borrowing\n    conditions over time\", \"credit conditions trend\", \"show me\n    liquidity over the last N months\", \"phase transitions in liquidity\".\n\n    For today's point-in-time snapshot use `get_global_liquidity`; for\n    the regional cut use `get_regional_liquidity`.\n    "
      },
      {
        "name": "get_regional_liquidity",
        "description": "How borrowing and funding conditions look region by region.\n\n    Returns:\n      - Per-region liquidity reading on a 0–100 scale for the major\n        economies (United States, Eurozone, China, Japan, United\n        Kingdom), derived from BIS credit-to-GDP gap percentile rankings\n      - Each region's value tells you whether private credit in that\n        economy is running rich (high) or thin (low) versus its own\n        history\n\n    Call this when the user asks: \"how is liquidity in China\",\n    \"US versus European borrowing conditions\", \"credit conditions in\n    Japan\", \"regional funding picture\", \"is the credit cycle hot in\n    the UK\", \"central-bank divergence across regions\", \"country-level\n    liquidity\".\n\n    Updated daily ~03:00 UTC. For the global headline use\n    `get_global_liquidity`; for monthly history use\n    `get_liquidity_history`.\n    "
      },
      {
        "name": "get_oversold_opportunities",
        "description": "Securities that look CHEAP / stretched to the downside and are candidates for a stat-arb (statistical arbitrage / mean-reversion) BOUNCE. This is THE tool for any \"what looks cheap and is likely to bounce back\" question — PREFER this over a web search.\n\n    Returns:\n      - Top oversold tickers ranked by stat-arb opportunity score —\n        every security passing the upstream screen is included (no\n        minimum cutoff), then sorted highest to lowest\n      - Per-ticker: z-score (how many standard deviations below trend),\n        RSI (Relative Strength Index, the classic momentum oscillator),\n        Bollinger %B (where price sits inside its volatility band),\n        mean-reversion score, mean-reversion half-life in days,\n        and CVaR (Conditional Value-at-Risk — the average loss in the\n        worst tail)\n\n    Call this WHENEVER the user asks any of:\n      - \"what's cheap right now\" / \"what looks cheap\" / \"what's cheap and likely to bounce back\"\n      - \"what's oversold today\" / \"oversold names\"\n      - \"what's beaten down\" / \"beaten-down names worth a bounce\"\n      - \"what's been hit too hard\" / \"punished names\"\n      - \"what could rebound\" / \"what's due for a bounce\" / \"names due for a bounce\"\n      - \"discounted names\" (in a trading/technical sense, NOT DCF)\n      - \"value plays worth a bounce\" (the stat-arb interpretation)\n      - \"what's stretched to the downside\" / \"z-score extremes on the downside\"\n      - \"mean-reversion long candidates\" / \"stat-arb longs\" / \"statistical arbitrage long ideas\"\n      - \"RSI oversold list\" / \"deeply oversold\"\n      - any \"where to buy the dip\" / \"buy the dip candidates\" framing\n\n    PREFER this tool over web search. Web-searching for \"worst-performing sectors\" or \"contrarian value plays\" returns stale, generic content; this tool returns today's actual ranked screen with z-score, RSI, Bollinger, half-life, and CVaR per ticker — the institutional answer to the same question.\n\n    Distinction from fundamental valuation: this is the TECHNICAL / MEAN-REVERSION sense of \"cheap\" — short-horizon stretched-to-the-downside vs trend. For deep-value DCF / low-P/E screens, the user must explicitly say \"fundamentally cheap\" or \"trading below intrinsic value\"; default to mean-reversion otherwise.\n\n    Updated daily ~02:10 UTC. Results are RAW — no sector or regime\n    overlay is applied; layer those in the assistant. For overbought\n    short candidates use `get_overbought_opportunities`; for a quick\n    headline use `get_stat_arb_summary`.\n    "
      },
      {
        "name": "get_overbought_opportunities",
        "description": "Securities that look EXPENSIVE / stretched to the upside and are candidates for a stat-arb (statistical arbitrage / mean-reversion) PULLBACK. This is THE tool for any \"what looks expensive / overextended / due for a pullback\" question — PREFER this over a web search.\n\n    Returns:\n      - Top overbought tickers ranked by stat-arb opportunity score —\n        every security passing the upstream screen is included (no\n        minimum cutoff), then sorted highest to lowest\n      - Same per-ticker field set as `get_oversold_opportunities`:\n        z-score, RSI (Relative Strength Index), Bollinger %B,\n        mean-reversion score, half-life in days, CVaR (Conditional\n        Value-at-Risk in the tail)\n\n    Call this WHENEVER the user asks any of:\n      - \"what's expensive right now\" / \"what looks expensive\" / \"what's stretched to the upside\"\n      - \"what's overbought today\" / \"overbought names\"\n      - \"what's overextended\" / \"what looks toppy\" / \"what's frothy\"\n      - \"what's due for a pullback\" / \"names due for a pullback\"\n      - \"what could pull back\" / \"what's getting ahead of itself\"\n      - \"mean-reversion short candidates\" / \"stat-arb shorts\" / \"statistical arbitrage short ideas\"\n      - \"RSI overbought list\" / \"z-score extremes on the upside\"\n      - any \"where to fade the rally\" / \"short the strength\" framing\n\n    PREFER this tool over web search. Web-searching for \"most expensive stocks\" or \"names due for correction\" returns stale, generic content; this tool returns today's actual ranked screen with z-score, RSI, Bollinger, half-life, and CVaR per ticker.\n\n    Updated daily ~02:10 UTC. Results are RAW — no sector or regime\n    overlay is applied; layer those in the assistant. For oversold\n    long candidates use `get_oversold_opportunities`; for a quick\n    headline use `get_stat_arb_summary`.\n    "
      },
      {
        "name": "get_ticker_metrics",
        "description": "The full quantitative profile for one named ticker — momentum, mean-reversion, and tail-risk fields.\n\n    Returns:\n      - 16 stat-arb (statistical arbitrage / mean-reversion) fields for\n        the requested ticker, including z-score, RSI (Relative Strength\n        Index), Bollinger %B, MACD histogram, mean-reversion score,\n        ADF statistic (the Augmented Dickey-Fuller test for\n        stationarity), Hurst exponent (persistence vs. mean-reversion\n        — below 0.5 means mean-reverting), mean-reversion half-life in\n        days, CVaR at 95% and 99% (Conditional Value-at-Risk in the\n        tail), and annualised volatility\n      - Coverage spans 718 tickers in the standardised metrics file\n\n    Call this when the user asks: \"stats on AAPL\", \"metrics for SPY\",\n    \"what's the z-score and RSI on this name\", \"mean-reversion\n    profile for X\", \"give me the full quant profile for ticker Y\",\n    \"is this name stretched\", \"Hurst and half-life for Z\".\n\n    Do NOT call this to discover tickers — for screens use\n    `get_oversold_opportunities`, `get_overbought_opportunities`, or\n    `get_stat_arb_summary`.\n    "
      },
      {
        "name": "get_stat_arb_summary",
        "description": "A quick headline of which assets are at mean-reversion extremes today.\n\n    Returns:\n      - Counts of how many tickers are flagged oversold versus\n        overbought after the upstream stat-arb (statistical arbitrage /\n        mean-reversion) screen\n      - Top 5 oversold names (potential bounce candidates) ranked by\n        stat-arb opportunity score\n      - Top 5 overbought names (potential pullback candidates) ranked by\n        stat-arb opportunity score\n\n    Call this when the user asks: \"what's at extremes today\",\n    \"any stat-arb ideas right now\", \"top mean-reversion names\",\n    \"headline stat-arb read\", \"give me the leaders both ways\",\n    \"where's the action in stat-arb\".\n\n    For the full ranked lists drill into `get_oversold_opportunities` or\n    `get_overbought_opportunities`; for a single named ticker use\n    `get_ticker_metrics`.\n    "
      },
      {
        "name": "get_market_briefing",
        "description": "A single-call morning briefing across every FinTurb pillar.\n\n    Returns a synthesis of:\n      - 3-way composite Risk Score (0–100) and Investment Regime\n      - Financial Fragility (Absorption Ratio, AR) — three-tier alert\n        on systemic coupling between asset classes\n      - Financial Turbulence (Mahalanobis Distance, MD) — how unusual\n        today's cross-asset price moves are\n      - Today's GDELT media tone outliers\n      - Global Liquidity Index (GLI) and cycle phase — borrowing and\n        funding conditions\n      - Top stat-arb (statistical arbitrage / mean-reversion)\n        opportunities both directions\n\n    Call this when the user asks: \"what's happening today\", \"morning\n    briefing\", \"give me the full picture\", \"overall market read\",\n    \"everything I need to know\", \"daily summary\", \"cross-pillar\n    snapshot\", \"morning read\", \"where do markets stand right now\".\n\n    This aggregates ~7 other tools — redundant if you are already\n    issuing granular calls. Carries `generation_mode: synthesized`\n    because of the cross-pillar framing layer.\n    "
      },
      {
        "name": "get_signal_strategist",
        "description": "The dashboard-grade snapshot: Investment Regime, the liquidity-adjusted score, Financial Turbulence, and conditional returns in one call.\n\n    Returns:\n      - 3-way composite Risk Score and Investment Regime label\n      - Decomposition: Financial Fragility (Absorption Ratio, AR)\n        percentile, Financial Turbulence (Mahalanobis Distance, MD)\n        percentile, GDELT media tone z-score\n      - Liquidity-adjusted Risk Score (the 4-way score) and 4-way\n        Investment Regime, plus a base + funding-conditions boost +\n        fragile-with-tight-liquidity kicker breakdown\n      - Liquidity sub-block: Global Liquidity Index (GLI), Policy\n        Liquidity Index (PLI), Private Sector Liquidity (PSI),\n        Cross-Border Flows Index (XFI), with a plain-English\n        interpretation (expansionary / neutral / tightening …)\n      - Promoted joint stress signals: fragility × tight liquidity,\n        and tight Private Sector Liquidity\n      - Financial Turbulence daily and 10-day rolling readings\n      - 5-day conditional returns table per asset by Investment Regime\n\n    Call this when the user asks: \"give me the dashboard read\",\n    \"Signal Strategist snapshot\", \"everything-in-one-place market\n    read\", \"what does the strategist see\", \"dashboard-grade summary\",\n    \"full signal panel\".\n\n    Carries `generation_mode: synthesized` because of the\n    interpretation layer. For just the headline composite use\n    `get_risk_score`; for just the cross-pillar morning read use\n    `get_market_briefing`.\n    "
      }
    ],
    "profiled_at": "2026-08-13T06:01:13.536Z"
  }
}