Traderspy Market Screener

TraderSpy Market Screener

Two tools, one vocabulary. screen_symbols evaluates up to three AND-ed conditions across the most-traded pairs (or a list you give it) on one timeframe, in ONE quota unit. backtest_condition takes the same conditions, one symbol and one timeframe, and reports what price did after every past occurrence — with the unconditional baseline so the edge is separated from the tape's drift.

Together they answer the two questions traders actually ask: "what fits this pattern right now?" and "has this pattern meant anything before?"

When to Use

• Use when the user wants to find, filter, rank or compare several coins by technical conditions: "which coins are oversold on the 4h", "what is above its 200 EMA with rising volume", "show me Bollinger squeezes", "find me setups".
• Use for side-by-side comparison tables such as "compare BTC, ETH and SOL".
• Use when the user asks what happened after a condition in the past: "how did ETH do after RSI dropped below 30", "is a golden cross on BTC daily actually bullish".
• Never answer these by calling get_technical_indicators coin by coin. For a deep read of one coin use @traderspy-technical-analysis.

The condition vocabulary

A condition is { metric, op, value, period?, period2? }. op is lt / gt (latest value) or crossAbove / crossBelow (a one-bar event: the previous bar was on the other side).

Periods clamp to 2–200. Conditions are AND-ed; there is no OR — run two scans for an OR and merge. Unknown metrics are rejected, so stick to the table (the full recipe list is in references/condition-cookbook.md).

Screening (screen_symbols)

Arguments: interval (default 4h), conditions (≤ 3), universe (5–100 most-traded by 24h volume, default 50) OR symbols (≤ 100, explicit), limit (≤ 50 rows), sortBy volume / change24h / metric, sortOrder.

Choose the timeframe from the user's horizon: intraday → 1h (or 15m), swing → 4h, position → 1d. Widen universe to 100 when the user wants small caps or the first scan matched little.

Every result row carries the metric values under their labels (values["RSI(14)"]), plus price, change24hPct, volume24hUsd, bias, trend, rsi14, adx14, atrPct, volumeRatio, squeeze. When matched > returned, say so and offer to raise limit.

Comparison mode: symbols with no conditions returns every listed symbol as a table — this is how you answer "compare BTC, ETH and SOL" or "how do my five coins look on the daily".

Translate intent to conditions before calling, and say what you translated it to:

• "oversold" → rsi lt 30 (or 35 for a wider net); "deeply oversold" add bbPercentB lt 0
• "overbought" → rsi gt 70
• "in an uptrend" → priceVsEma gt 0 period 200 + supertrend gt 0
• "with rising volume" → volumeRatio gt 1.5
• "squeezing" → bbWidthPct lt 4 on 4h (lower on 1h) — then sort by metric ascending
• "dumped today" → changePct lt -5 period 24 on 1h, or period 6 on 4h
• "golden cross" → emaSpread crossAbove 0 period 50 period2 200 on 1d

Backtesting (backtest_condition)

Arguments: symbol, interval, conditions (same vocabulary), horizons in bars (≤ 4; defaults ≈ 4h / 1d / 3d: 1h → [4, 24, 72], 4h → [6, 18, 42], 1d → [1, 3, 7]).

The study runs over the whole stored tape — up to 1000 candles, so roughly 41 days on 1h, 166 days on 4h, 3 years on 1d. An "occurrence" is the FIRST bar of each run where the condition held (ten consecutive oversold bars are one episode). For each horizon you get samples, avgReturnPct, medianReturnPct, winRatePct, avgMaxUpPct / avgMaxDownPct (average best and worst excursion, wick-accurate), bestPct / worstPct, baselineAvgReturnPct (every bar on the same tape) and edgePct = average − baseline. Also activeNow, currentValues, lastOccurrence, and recent[] with the last five episodes and their realised returns.

How to read it honestly:

• Edge and sample size travel together. edgePct +1.8 on 27 samples is a statement; +6 on 4 samples is an anecdote, and the tool says so in warnings. Never quote the edge alone.
• Median vs average: a positive average with a negative median means a few big winners carried it. Say which.
• Excursions are the risk picture: avgMaxDownPct −5.1 on a "bullish" setup means the average episode went 5% against you before the horizon ended. That belongs next to the win rate.
• Horizons that disagree (positive at 1d, negative at 3d) usually mean a bounce that fades — report the shape, do not pick the flattering horizon.
• Recent episodes newer than a horizon are excluded from that horizon (null in recent), never counted as zero.
• Coverage limits what the study can see: 41 days of 1h data contains one market regime. A 1d study is the only one that spans cycles.