chainvectorSignalsSnapshot

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

With no annotations, the description carries the full burden. It discloses the composite nature and that all data is 'sampled at the same instant,' which is useful. However, it does not mention the return format, whether authentication is required, or error behavior, leaving gaps.

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

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

Two sentences, information-dense with no redundant wording. It front-loads the tool's purpose and lists the included signals efficiently, earning each sentence's place.

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

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

For a composite snapshot tool with no output schema, the description comprehensively enumerates the signal components and the intended pre-trade use case. It lacks explicit output structure but covers purpose, scope, and timing well, especially given sibling tools exist for individual signals.

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

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

The schema provides 100% coverage of both parameters, including descriptions for symbol and min_notional. The description's mention of 'whale threshold' mirrors the schema without adding new meaning. Per calibration, baseline 3 applies when schema does the heavy lifting.

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

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

The description clearly defines this as a one-call bot decision snapshot for a base asset, listing concrete components (momentum scorecard, order-book imbalance, whale pressure, liquidation cascade risk, OI-weighted funding, squeeze gauge). Its 'snapshot' framing and aggregation of multiple signals distinguishes it from single-signal siblings like chainvectorMomentum and chainvectorSignalsHistory.

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

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

The description explicitly states the intended use case: reading the whole signal stack 'before a trade' in the 'cheapest way,' which implies it is best used when wanting a consolidated overview rather than individual metrics. It does not name alternative tools or exclusions, but the context is clear enough.

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