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).

Metric	Default period	Unit / meaning
`rsi`	14	0–100
`stochastic`	14, %D 3	slow %K, 0–100
`cci`	20	Commodity Channel Index (±100 typical bands)
`mfi`	14	0–100, volume-weighted RSI
`williamsR`	14	−100…0 (−80 oversold, −20 overbought)
`adx`	14	trend strength; > 25 strong, < 20 absent
`roc`	12	rate of change, %
`macdHistogram`	12, 26 (signal 9)	histogram in price units; `crossAbove 0` = bullish MACD cross
`atrPct`	14	ATR as % of price — volatility
`volumeRatio`	20	bar volume ÷ average of the previous N bars
`bbPercentB`	20 (2σ)	0 = lower band, 1 = upper band; < 0 or > 1 = outside
`bbWidthPct`	20	band width as % of the middle — small = squeeze
`priceVsEma`	50	% distance of close from EMA(period); > 0 above
`emaSpread`	50, 200	% of EMA(period) over EMA(period2); `crossAbove 0` = golden cross
`supertrend`	10 (×3)	+1 up-trend, −1 down-trend
`changePct`	24	% change of close over the last N BARS (on 1h, 24 = one day)
`price`	—	close

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 useful, but volume rank does not identify market capitalization and does not cover all small caps.

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 documented defaults: 1h → [4, 24, 72] (4h/1d/3d), 4h → [6, 18, 42] (1d/3d/7d), 1d → [1, 3, 7] (1d/3d/7d)).

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 has longer coverage, but three years does not establish robustness across full market cycles.

Workflows

"What's oversold right now?" → one screen_symbols. Present the table, then (optional, one more call) backtest_condition the same condition on the top match so the answer carries "and here is what that has meant on this coin before".

"Find me setups" / "watchlist" → decide the archetype with the user in one line (mean-reversion vs trend-continuation vs breakout), run one scan per archetype (2–3 calls), and present each list with the conditions it was built from. Do not promise an outcome for any row.

"Is X actually bullish?" → one backtest_condition on the coin and timeframe in question; if the user names no coin, BTC on 1d is the most meaningful default and say why (longest tape).

"Compare A, B, C" → screen_symbols with symbols, no conditions, on the timeframe they care about. Add get_derivatives (technical-analysis) only if the question includes funding or positioning.

Presenting

Screen: state the conditions in words and in the tool's labels, the timeframe, and the universe ("50 most-traded pairs"), then one row per symbol:

Backtest: one header line (symbol, timeframe, condition, occurrences, coverage), a horizon table —

— then the last episodes and whether the condition is active now. Close with the sample-size caveat in your own words.

Study limits

Report timestamp, venue, instrument, closed-versus-open candle status and actual coverage. Price returns are not net strategy returns: fees, spread, slippage, funding, leverage and liquidation are not accounted for unless the tool explicitly says otherwise. Baseline subtraction is descriptive, not a statistically established causal edge. Overlapping horizons, current-universe survivorship and repeated condition searches can bias results; use separate out-of-sample data before treating a pattern as robust. Never fabricate missing observations or assume freshness.

Conduct

A screen describes the returned chart snapshot; a backtest is a sample of what followed in the past. Neither is a recommendation. Present the evidence, note what would invalidate the setup, and leave the trade — and the sizing — to the user.
Never turn "70% win rate on 12 samples" into a forecast; historical stats describe their sample.
Nothing in this connector trades — no order, close, transfer or withdrawal tool exists by design. If asked to execute, say so plainly; the decision and the trade stay with the user.
Quote only what the tools returned; when a symbol is missing from the universe say it was not scanned rather than implying it failed the filter.
When a specific trade idea is under discussion, end with one plain sentence that crypto derivatives are high-risk and this is market information, not financial advice.

Examples

Which coins are oversold on the 4h?
Run the screener: RSI under 30 and ADX above 25 on the 4h, top 100 by volume.
Compare BTC, ETH and SOL on the daily.
Historically, what happened on SOLUSDT 4h after RSI crossed above 30? Compare it against the baseline over the same tape.

Limitations

Needs the hosted TraderSpy MCP server connected in the client (https://mcp.traderspy.app/mcp, Streamable HTTP), authorized with OAuth or a personal key from https://traderspy.app/mcp. A free TraderSpy account is enough. Without the server the skill has no data to work from.
Tool calls are metered; confirm current plan quotas and tool schemas before use rather than treating historical tier numbers as current.
Every tool is read-only. Nothing here places, closes or modifies an order, and there is no withdrawal or transfer tool.
The output is market data and analysis for the user's own research, not investment advice.
Conditions are AND-ed, at most three per scan, from the fixed metric list above. An OR needs two scans.
A scan covers up to the 100 most-traded pairs or an explicit list of up to 100 symbols. A backtest sees at most 1000 stored candles, about 41 days on 1h.

Related Skills

@traderspy-technical-analysis (called technical-analysis in the text above, its upstream ID) - one coin in depth, and get_derivatives for funding and positioning
@traderspy-market-briefing - a market overview that includes a movers scan