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veroq_screener

Screen stocks or crypto by combining technical indicators, sentiment, and fundamental filters to find assets matching your criteria (e.g., oversold tech stocks). Returns symbol, price, change%, RSI, MACD signal, sentiment, and volume.

Instructions

Screen stocks or crypto by combining technical indicators, sentiment, and fundamental filters.

WHEN TO USE: To find assets matching specific criteria (e.g. oversold tech stocks, high-volume bearish crypto). Use veroq_screener_presets for pre-built strategies. RETURNS: Matching assets with symbol, price, change%, RSI, MACD signal, sentiment, and volume. COST: 5 credits. EXAMPLE: { "sector": "Technology", "rsi_below": 30, "sentiment": "bearish", "limit": 10 }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asset_typeNoAsset type to screen (e.g. stock, crypto)
sectorNoSector filter (e.g. Technology, Healthcare, Energy)
rsi_belowNoRSI upper bound (e.g. 30 for oversold)
rsi_aboveNoRSI lower bound (e.g. 70 for overbought)
sentimentNoSentiment filter (e.g. bullish, bearish, neutral)
macd_signalNoMACD signal filter: buy or sell
earnings_within_daysNoOnly assets with earnings within N days
price_minNoMinimum price filter
price_maxNoMaximum price filter
min_volumeNoMinimum average daily volume
sortNoSort field (e.g. rsi, sentiment, market_cap, volume)
limitNoMax results (default 20)
Behavior4/5

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

No annotations provided, so description carries full burden. It adds 'COST: 5 credits' and lists return fields. For a screening tool, this is sufficient; no side effects or authorization needs are implied, and it does not contradict any annotations.

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

Conciseness5/5

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

Description is well-structured with sections (WHEN TO USE, RETURNS, COST, EXAMPLE), concise, and front-loaded. Every sentence adds value.

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?

No output schema, but description lists return fields. Given the 12 optional parameters and complexity, the description covers purpose, usage, cost, and example, making it sufficiently complete for agent selection and invocation.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The example usage (`{ 'sector': 'Technology', 'rsi_below': 30, ... }`) adds concrete context that helps an agent understand parameter combinations beyond the schema.

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 clearly states the verb 'screen' and resource 'stocks or crypto', and distinguishes from sibling 'veroq_screener_presets' by directing users to that tool for pre-built strategies.

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?

Includes a dedicated 'WHEN TO USE' section that gives concrete examples (e.g., oversold tech stocks) and explicitly mentions the alternative tool for pre-built strategies.

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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