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get_trading_signals

Generate trading signals for assets like BTC and ETH, with adjustable confidence thresholds and optional prediction market momentum for refined recommendations.

Instructions

Generate trading signals for specified assets.

Args: assets: List of assets to analyze (default: BTC, ETH) include_prediction_markets: Include prediction market momentum min_confidence: Minimum confidence threshold (0-100)

Returns: Dict containing signals, metadata, and recommendations

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetsNo
min_confidenceNo
include_prediction_marketsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are present, so the description must disclose behavioral traits fully. It only describes a generic 'generate' action without indicating side effects, safety, or performance implications (e.g., computational cost, data source freshness).

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 follows a clear docstring pattern (summary, Args, Returns) with no extraneous text. However, it could be slightly more concise by omitting the Returns section if the output schema is rich, but it remains efficient.

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

Completeness3/5

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

The description covers the basics but lacks details on error handling, rate limits, or prerequisites. The return format is vague ('Dict containing signals, metadata, and recommendations'), though an output schema may compensate. Usage guidelines are missing.

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

Parameters5/5

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

The description provides default values and contextual meaning for all three parameters (assets default to BTC/ETH, min_confidence range 0-100, include_prediction_markets enables momentum). This adds significant value beyond the schema's bare titles and types.

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 'Generate trading signals for specified assets', which is a specific verb+resource combination. It distinguishes from siblings like get_signal_accuracy or analyze_all_markets by focusing on signal generation.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. Sibling tools like get_signal_accuracy or execute_arbitrage_trade have related but distinct purposes, but no exclusion criteria or context are provided.

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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