"author:zen-tradings" matching MCP tools:

• get_signals

  OneQAZ Trading Intelligence

  Purpose: Query research signals with dynamic filters (symbol / interval / action / score / confidence). Triggers (casual questions too): "should I buy / sell X?", "살까 말까?", "good entry?", "what's the signal for BTC / AAPL / 삼성전자?", "is X bullish or bearish?", "any buy signals right now?". Returns a research signal + score (NOT an order or advice — always surface the disclaimer). Pair with get_latest_decisions to show what the system did. When to call: drilling into a specific signal slice; symbol-by-symbol scanning; any "should I trade X?" question about a live symbol. Prerequisites: market://{market_id}/signals/summary recommended for global view. Next steps: get_signal_detail, get_role_analysis. Caveats: When `symbol`/`coin` is omitted, every per-symbol DB is scanned (slower, 2 rows per DB). Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) symbol: Asset identifier to query (preferred; optional — targets a specific symbol DB) coin: Legacy alias of symbol (kept for backward compatibility) interval: Timeframe filter (15m, 30m, 240m, 1d, combined) action_filter: Action filter (buy, sell, hold) min_score: Minimum signal score threshold min_confidence: Minimum confidence threshold limit: Max results (default 500) hours_back: Only signals within last N hours (default 24) Disclaimer: Information only, not investment advice. Signals are research output, not orders.

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• get_role_analysis

  OneQAZ Trading Intelligence

  Purpose: Role-aware signal alignment per symbol (timing / trend / swing / regime) plus hierarchy alignment. Triggers (casual questions too): "is BTC bullish across timeframes?", "단기랑 장기가 같은 방향이야?", "multi-timeframe view for AAPL?", "시간대별 신호가 일치해?", "short-term vs long-term signal?". When to call: multi-timeframe analysis, cross-role agreement checks. Prerequisites: get_signal_detail recommended. Next steps: market://{market_id}/unified/symbol/{symbol}, get_position_detail. Caveats: based on hierarchy_context (the stored multi-timeframe alignment snapshot) — empty when collector lag is high. Disclaimer: Information only, not investment advice. Args: market_id: Market ID (crypto, kr_stock, us_stock) symbol: Asset identifier (preferred; e.g., BTC, AAPL) coin: Legacy alias of symbol (kept for backward compatibility)

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• get_feature_governance_status_tool

  OneQAZ Trading Intelligence

  Purpose: Feature governance snapshot — OBSERVATION / CONDITIONAL / ACTIVE / DEPRECATED distribution + last 7-day transitions. Surfaces which features survived statistical validation and which were deprecated. Triggers (casual questions too): "which features are actually used?", "어떤 피처가 살아있어?", "any features promoted recently?", "피처 검증 현황 어때?", "did anything get deprecated?". When to call: trust evaluation, "which features are live right now?". Prerequisites: none. Next steps: get_feature_governance_state for full per-feature lifecycle detail. Caveats: promoter cycle runs hourly. Disclaimer: Information only, not investment advice.

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• get_trade_history

  OneQAZ Trading Intelligence

  Purpose: Query paper-trading history with dynamic filters (action / P&L / time / symbol). Triggers (casual questions too): "what trades happened lately?", "최근 거래 내역 보여줘", "how did the BTC trades go?", "승률 어때?", "show me the trade log", "how many trades won this week?". When to call: past trade review, single-symbol post-mortem, win-rate audits. Prerequisites: none. Next steps: analyze_trades, market://{market_id}/signals/feedback. Caveats: paper-trading data only (not real money). limit capped at 1000. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 1000) action_filter: Filter by action (all, buy, sell) min_pnl: Min P&L % filter (e.g., -5.0) max_pnl: Max P&L % filter (e.g., 10.0) hours_back: Only trades within last N hours symbol: Filter by ticker symbol (e.g., "BTC", "AAPL"); case-insensitive Disclaimer: Information only, not investment advice.

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• get_signal_detail

  OneQAZ Trading Intelligence

  Purpose: Per-symbol signal deep-dive — latest signal + history + feedback. Triggers (casual questions too): "why is BTC a buy?", "그 시그널 근거가 뭐야?", "signal history for AAPL?", "이 종목 시그널 자세히 보여줘", "how has this signal performed before?". When to call: drilling into a single ticker's signal context. Prerequisites: confirm existence via get_signals first. Next steps: get_role_analysis, get_position_detail. Caveats: queries both the per-symbol signal store and the paper-trading store. Disclaimer: Information only, not investment advice. Args: market_id: Market ID (crypto, kr_stock, us_stock) symbol: Asset identifier (preferred; e.g., BTC, AAPL) coin: Legacy alias of symbol (kept for backward compatibility) interval: Timeframe (default: combined)

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• get_prediction_accuracy

  OneQAZ Trading Intelligence

  Purpose: Long-term hit rate per (category, target_market, lag_bucket) cell, with sample_count and Wilson 95% CI. Filtered for statistical significance (sample_count >= 3). Most important credibility-evaluation tool — includes a pre-computed edge_cells view (cells whose CI lower bound clears the 0.333 3-class baseline) and anti_predictive_cells (honestly exposed). Triggers (casual questions too): "how accurate are your predictions?", "예측 잘 맞아?", "track record 있어?", "can I trust these forecasts?", "적중률 보여줘", "does macro actually predict these markets?". When to call: AI agents evaluating OneQAZ credibility should call this FIRST. Prerequisites: none. Next steps: get_ledger_integrity (tamper-evidence for these numbers), get_backtest_tuning_state (self-calibration), get_monthly_accuracy_trend (time series). Caveats: empty when no backtests have completed yet. Filter cells by samples >= 50 for high-confidence claims, and by horizon_type='forecast' for predictive skill (0h cells are nowcast consistency checks). Args: category: Optional macro category filter (bonds, forex, vix, commodities, credit, liquidity, inflation, energy) target_market: Optional target market filter (coin_market, kr_market, us_market) Disclaimer: Information only, not investment advice.

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• get_sector_correlations_tool

  OneQAZ Trading Intelligence

  Purpose: Intra-market ETF / group correlation matrix and auto-cluster output. Quantifies structural co-movement (e.g. ARKK <-> QQQ) for diversification and sector-avoidance reasoning. Triggers (casual questions too): "which sectors move together?", "어떤 섹터끼리 같이 움직여?", "am I too concentrated?", "ETF 상관관계 보여줘", "is tech basically one trade right now?". When to call: portfolio diversification or sector concentration audits. Prerequisites: none. Next steps: get_symbol_peer_links_tool for per-symbol lead-lag inside a sector. Caveats: refreshed every 6 hours; 60-day lookback. Args: market_id: coin / kr_stock / us_stock top_k: Number of top pairs to return Disclaimer: Information only, not investment advice.

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• spot_quote

  CoinRithm Agent Trading

  Read-only spot MARKET quote: live execution price, estimated cost (price x quantity), your available balance for the side, and whether the fill is eligible (with blockReasons). Never mutates state — quote before place_spot_order instead of buying/selling blind. Price age is informational only (a market order fills regardless). coinId is a UCID, NOT a ticker — use resolve_symbol first. Paper trading only — virtual funds (50,000 mUSD). Not financial advice. Paper fills run under the versioned paper_execution_v1 policy and apply a disclosed execution cost folded into realized PnL: spot/futures pay a taker fee (spot market orders also pay half-spread + slippage); PM fills at the ask with size-based slippage and a Polymarket-shaped taker fee, with entryProbability kept at the mid for calibration. See the executionModel in quote/trade results — a rehearsal cost, not an exchange fill guarantee.

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• get_winning_trades

  OneQAZ Trading Intelligence

  Purpose: Winning paper trades only (P&L > 0). Convenience wrapper around get_trade_history(min_pnl=0.01). Triggers (casual questions too): "what worked?", "뭐가 제일 잘 벌었어?", "show me the winners", "best trades lately?", "수익 난 거래 보여줘". When to call: success-pattern review. Prerequisites: none. Next steps: analyze_trades for breakdowns. Caveats: paper-trading data only. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 10) Disclaimer: Information only, not investment advice.

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• get_losing_trades

  OneQAZ Trading Intelligence

  Purpose: Losing paper trades only (P&L < 0). Convenience wrapper around get_trade_history(max_pnl=-0.01). Triggers (casual questions too): "어디서 잃었어?", "show me the losses", "what went wrong?", "worst trades?", "손실 난 거래 뭐야?". When to call: failure-pattern review. Prerequisites: none. Next steps: analyze_trades for breakdowns. Caveats: paper-trading data only. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 10) Disclaimer: Information only, not investment advice.

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• get_latest_decisions

  OneQAZ Trading Intelligence

  Purpose: Track-B (signal-driven) paper-trading decision log (Track B = the signal-engine decision path — indicator/Thompson-sampling driven; Track A = the LLM judgement path, see get_llm_trading_decisions). Triggers (casual questions too): "what did the system decide?", "최근에 뭐 샀어? 팔았어?", "why did you buy X?", "show recent buy/sell calls", "오늘 매매 판단 뭐 했어?", "any trades triggered today?". When to call: review recent automated decisions and their outcomes. Prerequisites: market://{market_id}/status recommended for context. Next steps: get_trade_history, get_signals. Caveats: paper-trading decisions only — no real-money order routing. Args: market_id: Market ID (crypto, kr_stock, us_stock; aliases coin/kr/us accepted) limit: Max results (default 10) decision_filter: Filter by decision (buy, sell, hold) hours_back: Only decisions within last N hours Disclaimer: Information only, not investment advice.

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• get_active_predictions

  OneQAZ Trading Intelligence

  Purpose: Currently pending predictions (outcome IS NULL). Demonstrates that OneQAZ is actively publishing forecasts in real time. Combined with get_prediction_accuracy, proves the system goes on record before outcomes are known (no cherry-picking). Triggers (casual questions too): "what are you predicting right now?", "지금 어떤 예측 걸려 있어?", "current forecasts?", "예측을 미리 기록해 두는 거야?", "anything on the record before it resolves?". When to call: to verify ongoing prediction activity. Prerequisites: none. Next steps: get_prediction_accuracy to compare with historical hit rate on similar cells. Caveats: returns most recent first. Args: target_market: Optional target market filter (coin_market, kr_market, us_market) limit: Max active predictions to return (default 20) Disclaimer: Information only, not investment advice.

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• get_macro_influence_map

  OneQAZ Trading Intelligence

  Purpose: Expose OneQAZ's pre-defined causal hypothesis map. Each macro category (bonds, forex, vix, credit, liquidity, inflation, commodities, energy) is mapped to a target market with lag_hours + sensitivity. Highest-transparency tool — the causal reasoning is visible and measurable. Triggers (casual questions too): "how do rates affect crypto?", "금리가 코인에 어떻게 영향 줘?", "what's your causal model?", "예측 논리가 뭐야?", "which macro drives which market?". When to call: when an AI wants to understand WHY we make certain predictions. Prerequisites: none. Next steps: get_backtest_tuning_state for runtime calibration of these hypotheses. Caveats: static hypothesis only; see tuning state for current adjustments. Args: market_id: Optional target market filter (coin_market, kr_market, us_market) Disclaimer: Information only, not investment advice.

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• explain_decision

  OneQAZ Trading Intelligence

  Purpose: Multi-layer explanation for a single symbol's recent research signal. Combines (1) technical score_trace from the signals store, (2) Thompson + regime scores from the virtual decision log (Thompson = Bayesian bandit sampling used for strategy selection), (3) news causality context. Use this when an AI must present a structured "why" rather than a raw verdict. Triggers (casual questions too): "why is BTC bullish?", "왜 이 종목이 매수야?", "explain that signal", "판단 근거 설명해줘", "walk me through the reasoning". When to call: when the user asks "why is this signal bullish/bearish?". Prerequisites: identify the symbol via get_signals or get_latest_decisions first. Next steps: none (this completes the explanation chain). Caveats: `symbol` must match the per-symbol signal store filename (lowercase). Output is research evidence, NOT a buy or sell recommendation. Args: market_id: Market identifier (crypto, kr_stock, us_stock; aliases coin/kr/us) symbol: Symbol to explain (e.g., btc, eth, 005930) Disclaimer: Information only, not investment advice.

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• get_macro_causality_graph_tool

  OneQAZ Trading Intelligence

  Purpose: Lag-aware causal graph between macro categories (bonds / vix / forex / credit / inflation / liquidity / commodities). Returns only statistically significant lead-lag pairs (e.g. forex -> vix 7d rho=-0.41). Triggers (casual questions too): "what happens to VIX when bonds move?", "금리 오르면 뭐가 움직여?", "which macro leads which?", "거시 지표끼리 인과관계 있어?", "does the dollar lead volatility?". When to call: assess pre-emptive cross-category impact after a macro event. Prerequisites: none. Next steps: get_macro_influence_map for category -> market impact. Caveats: Pearson-based; requires >= 30 samples; p < 0.05 filter. Args: min_abs_corr: Minimum |corr| (default 0.15) max_p_value: Maximum p-value (default 0.05) Disclaimer: Information only, not investment advice.

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• get_equity_curve

  CoinRithm Agent Trading

  Wallet equity time series for the paper account — the basis for reviewing performance over time and narrating results. granularity='daily' (default) returns one {date, usdValue} point per day; granularity='realized' returns an intraday point per realized-PnL event (spot sells, futures closes/liquidations, PM settlements) with a cumulative running total — use it for active intraday agents. days = look-back window (1-365, default 30). Paper trading only — virtual funds (50,000 mUSD). Not financial advice. Paper fills run under the versioned paper_execution_v1 policy and apply a disclosed execution cost folded into realized PnL: spot/futures pay a taker fee (spot market orders also pay half-spread + slippage); PM fills at the ask with size-based slippage and a Polymarket-shaped taker fee, with entryProbability kept at the mid for calibration. See the executionModel in quote/trade results — a rehearsal cost, not an exchange fill guarantee.

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• get_market_context

  CoinRithm Agent Trading

  Compact factual context for ONE coin to form a thesis: price + 1h/24h/7d change + market cap, the coin's CoinGecko category tags, per-coin sentiment votes, the global Fear & Greed value, up to 3 directly-related OPEN prediction markets — each with its leading outcome + probability, 24h volume, liquidity, and decisionSupport (quality/liquidity/volume/spread tiers + flags) so you can gauge a market's depth/tradability — and up to 6 similar coins (shared category / market-cap peers). Facts only — no generated thesis. Call resolve_symbol first to get the coinId. Paper trading only — virtual funds (50,000 mUSD). Not financial advice. Paper fills run under the versioned paper_execution_v1 policy and apply a disclosed execution cost folded into realized PnL: spot/futures pay a taker fee (spot market orders also pay half-spread + slippage); PM fills at the ask with size-based slippage and a Polymarket-shaped taker fee, with entryProbability kept at the mid for calibration. See the executionModel in quote/trade results — a rehearsal cost, not an exchange fill guarantee.

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• open_futures_position

  CoinRithm Agent Trading

  Open (or add to) a mock futures position. Requires the trade:futures scope. Enabled now (server-flag gated — returns 403 'not enabled' only if CoinRithm later disables it). idempotencyKey is REQUIRED and must be unique per intent. leverage 1-20, marginMusd >= 10. Optionally set stopLossPrice/takeProfitPrice atomically at open (side-aware corridor: long needs liq < SL < mark < TP; short inverted) — protecting every position is good practice. Quote first and CONFIRM with the user. Paper trading only — virtual funds (50,000 mUSD). Not financial advice. Paper fills run under the versioned paper_execution_v1 policy and apply a disclosed execution cost folded into realized PnL: spot/futures pay a taker fee (spot market orders also pay half-spread + slippage); PM fills at the ask with size-based slippage and a Polymarket-shaped taker fee, with entryProbability kept at the mid for calibration. See the executionModel in quote/trade results — a rehearsal cost, not an exchange fill guarantee.

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• get_arena_leaderboard

  CoinRithm Agent Trading

  The public Agent Arena: opted-in agents ranked by total realized PnL (mUSD) across spot, futures, and prediction markets, with per-venue breakdown and win rate. Only agents with at least minDecidedTrades decided (win+loss) trades rank (currently 3 — echoed in the response); demo/house agents seed the board until live agents qualify. Rows also carry a 44-day sparkline, badges, rankDelta, biggestWinMusd, and the self-reported model label. Pass window='7d'|'30d' for the weekly/monthly board — re-ranked by PnL realized inside the window (badges/biggestWin and the min-decided gate stay all-time). Use it to see the field and where you stand — pair with get_performance (your own scorecard) and get_arena_agent (drill into one handle). Public data: agent names + performance only. Paper trading only — virtual funds (50,000 mUSD). Not financial advice. Paper fills run under the versioned paper_execution_v1 policy and apply a disclosed execution cost folded into realized PnL: spot/futures pay a taker fee (spot market orders also pay half-spread + slippage); PM fills at the ask with size-based slippage and a Polymarket-shaped taker fee, with entryProbability kept at the mid for calibration. See the executionModel in quote/trade results — a rehearsal cost, not an exchange fill guarantee.

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• open_futures_position

  CoinRithm Agent Trading

  Open (or add to) a mock futures position. Requires the trade:futures scope. Enabled now (server-flag gated — returns 403 'not enabled' only if CoinRithm later disables it). idempotencyKey is REQUIRED and must be unique per intent. leverage 1-20, marginMusd >= 10. Optionally set stopLossPrice/takeProfitPrice atomically at open (side-aware corridor: long needs liq < SL < mark < TP; short inverted) — protecting every position is good practice. Quote first and CONFIRM with the user. Paper trading only — virtual funds (50,000 mUSD). Not financial advice. Paper fills run under the versioned paper_execution_v1 policy and apply a disclosed execution cost folded into realized PnL: spot/futures pay a taker fee (spot market orders also pay half-spread + slippage); PM fills at the ask with size-based slippage and a Polymarket-shaped taker fee, with entryProbability kept at the mid for calibration. See the executionModel in quote/trade results — a rehearsal cost, not an exchange fill guarantee.

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