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screen_symbols

Read-onlyIdempotent

Screen MANY crypto futures symbols at once on one timeframe — "which coins are oversold on 4h", "what is above its 200 EMA with rising volume", "show me squeezes". Give up to 3 AND-ed conditions from a fixed metric list (RSI, stochastic, CCI, MFI, Williams %R, ADX, ROC, MACD histogram, ATR%, volume ratio, Bollinger %B / width, price vs EMA, EMA spread, SuperTrend, change %, price) with lt / gt / crossAbove / crossBelow. Scans the most-traded symbols by 24h volume (default 50, max 100) or an explicit list; every row carries the metric values plus bias, trend, RSI, ADX, ATR% and 24h change. With NO conditions and explicit symbols it is a side-by-side comparison table ("compare BTC, ETH, SOL"). ONE quota unit however many symbols — always prefer this over calling get_technical_indicators in a loop.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoRows to return
sortByNovolume (24h quote volume), change24h, or metric (the first condition's metric). Default: metric when conditions are given, else volume.
symbolsNoExplicit symbols to scan (≤ 100, e.g. ["BTC","ETH","SOL"]). Omit to scan the most-traded symbols instead. With no `conditions`, every listed symbol is returned as a comparison table.
intervalNoCandle timeframe to evaluate on4h
universeNoHow many of the most-traded symbols (by 24h volume) to scan when `symbols` is omitted (max 100)
sortOrderNodesc
conditionsNoUp to 3 conditions, AND-ed. Examples: RSI oversold = {"metric":"rsi","op":"lt","value":30}; above the 200 EMA = {"metric":"priceVsEma","op":"gt","value":0,"period":200}; golden cross = {"metric":"emaSpread","op":"crossAbove","value":0,"period":50,"period2":200}; MACD bullish cross = {"metric":"macdHistogram","op":"crossAbove","value":0}; dumped 5% in a day = {"metric":"changePct","op":"lt","value":-5,"period":24}.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortByNo
matchedNoSymbols satisfying every condition (all scanned symbols when no conditions)
resultsNoOne row per matching symbol: { symbol, price, change24hPct, volume24hUsd, values { "<metric label>": value }, bias, trend, rsi14, adx14, atrPct, volumeRatio, squeeze }
intervalNo
returnedNo
universeNo{ source: top_by_volume | explicit, requested, scanned, missing[] }
warningsNo
sortOrderNo
conditionsNoHuman-readable conditions, e.g. "RSI(14) < 30"

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only and non-destructive behavior, so the description's job is lighter. It adds useful behavioral context: scans top symbols by 24h volume with a default of 50 and max of 100, 'ONE quota unit however many symbols', and a description of what each row carries. This goes beyond the annotations without contradicting them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one dense paragraph, but every sentence carries distinct information: purpose/examples, condition syntax, universe and row contents, comparison mode, and quota/alternative. It is front-loaded with the core purpose and not bloated, though it could be broken into clearer sentences or bullets.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 parameters, nested conditions, metric options), the description covers the essential operational aspects: both usage modes, default universe, row contents, quota cost, and the preferred alternative. The output schema and annotations fill the remaining details such as sorting, limit, and safety, so nothing critical is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is high (86%), so the baseline applies. The description largely restates what the schema already documents: the metric list, lt/gt/crossAbove/crossBelow operators, and the comparison-table behavior are all in the schema. It adds little new per-parameter meaning beyond what an agent would already see in the structured spec.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Screen MANY crypto futures symbols at once on one timeframe'. It further specifies the metric list, operators, and example queries, making the tool's purpose unmistakable. It also clearly differentiates from the sibling get_technical_indicators by emphasizing multi-symbol screening versus per-symbol loops.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly names the alternative and gives a preference rule: 'always prefer this over calling get_technical_indicators in a loop'. It also defines when the comparison-table mode applies ('With NO conditions and explicit `symbols`'), giving agents clear conditions for selecting between modes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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