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technical_scan

Scan market universes for technical setups (oversold, uptrend, volume spike) by downloading per-symbol candles across crypto, stock, or index markets.

Instructions

Scan a universe for a technical setup, not just a price move.

Args: signal: One of oversold, overbought, bullish, bearish, uptrend, downtrend, volume_spike, squeeze. market: "crypto" scans the most liquid Binance pairs; "stock"/"idx" scan the bundled ticker universes. universe: For stock/idx markets: "idx" or "us". interval: Candle size for the indicators. max_symbols: Symbols to examine (capped at 60 — each one costs a full candle download). limit: Rows to return.

Slower than the price screeners because it downloads candles per symbol; prefer a tighter max_symbols when you only need ideas, not coverage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
marketNocrypto
signalYes
intervalNo1d
universeNoidx
max_symbolsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It discloses that the tool downloads a full candle per symbol, caps max_symbols at 60, and is slower than price screeners. This provides concrete cost and constraint awareness, but it does not explicitly state read-only semantics, which is largely implied by 'scan.'

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?

The description is well-structured as a docstring with an Args section, front-loaded with the core purpose. Each parameter is explained succinctly, and the final performance note adds value without redundancy. No sentence is wasted.

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 presence of an output schema, return values need not be described. The description covers all six parameters, provides usage guidance, and explains performance trade-offs. It is sufficiently complete for an agent to select and invoke the tool correctly.

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 0%, so the description must compensate, and it does: signal lists all allowed values, market/universe explain their options, max_symbols notes the cap and cost, and limit is defined as rows returned. However, interval is only described as 'Candle size for the indicators' without listing valid values (e.g., 1h, 1d), which is a minor gap.

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 opens with 'Scan a universe for a technical setup, not just a price move,' which clearly identifies a specific verb (scan) and resource (universe). The phrase 'not just a price move' differentiates it from price-focused screeners, and the overall wording distinguishes it from siblings like technical_analysis and market_snapshot.

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

Usage Guidelines4/5

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

The description explicitly contrasts with price screeners ('Slower than the price screeners...') and advises using a tighter max_symbols when only ideas are needed. This gives clear when-to-use and performance context, though it does not name alternative tools like stock_screener or technical_analysis.

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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