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get_signal

Retrieve crypto trading signals with long/short/neutral direction, sentiment analysis, macro regime status, and signal strength metrics.

Instructions

Get composite trading signal for a crypto asset. Returns sentiment, macro regime (risk_on/risk_off), funding rate bias, OI delta, signal strength (0-100), confidence, and direction (long/short/neutral). Powered by SignalFuse.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesAsset ticker, e.g. BTC, ETH, SOL, DOGE, PEPE
credit_tokenNoOptional credit token for bulk-prepaid access
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It compensates well by detailing the return structure (signal strength 0-100, direction long/short/neutral, etc.) since no output schema exists, but fails to disclose operational constraints like rate limits, caching behavior, or explicit read-only status.

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 efficiently structured with the primary purpose front-loaded ('Get composite trading signal...'), followed immediately by the return value specification needed due to the missing output schema. The 'Powered by SignalFuse' attribution provides useful context without significant bloat.

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?

Given the lack of output schema, the description adequately enumerates all return fields (OI delta, confidence, etc.) necessary to understand the tool's output. However, it is incomplete regarding operational context (rate limits, authentication flows, error behaviors) that would typically be covered by annotations or additional description text.

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?

The input schema has 100% description coverage ('Asset ticker, e.g. BTC...' and 'Optional credit token for bulk-prepaid access'). The description adds no further parameter semantics beyond what the schema already provides, meeting the baseline expectation for high-coverage schemas.

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

Purpose4/5

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

The description states a specific action ('Get') and resource ('composite trading signal') with clear scope ('for a crypto asset'). It distinguishes from siblings get_regime and get_sentiment by enumerating the composite components returned (sentiment, macro regime, funding rate bias, etc.), though it does not explicitly differentiate from get_signal_batch.

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?

The description provides no explicit guidance on when to use this tool versus its siblings, particularly get_signal_batch for bulk operations or get_regime/get_sentiment for individual metrics. It also omits prerequisites such as API rate limits or authentication requirements beyond the optional credit_token parameter.

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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