get_derivatives_context

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 successfully identifies the data source (Deribit) and enumerates specific data categories returned, but omits critical behavioral details such as data freshness (real-time vs cached), rate limits, or whether historical data is available.

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?

The description efficiently packs specific data types, use case justification, and source attribution into two sentences. While 'Derivatives intelligence' is slightly abstract, the colon-delimited list immediately clarifies the concrete data points, minimizing cognitive load.

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?

Given the absence of parameters and output schema, the description adequately compensates by enumerating the specific metrics returned (funding rates, Greeks, open interest). For a simple data-retrieval tool, this provides sufficient context for invocation, though mentioning return structure format would further improve completeness.

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?

Per the evaluation rules, tools with zero parameters receive a baseline score of 4. The input schema contains no properties requiring semantic elaboration, so no additional descriptive compensation is needed beyond the baseline.

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 precisely identifies the resource (derivatives data) and specific sub-types (perpetual funding rates for BTC/ETH/SOL, options data including put/call ratios and max pain price, and leverage positioning). It clearly distinguishes from siblings like get_asset_context or get_macro_context by focusing exclusively on derivatives market data from Deribit.

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 provides implicit usage context by stating it is 'Critical for understanding market positioning and liquidation risk,' which hints at when to invoke the tool. However, it lacks explicit guidance on when to choose this over similar context-gathering siblings (e.g., get_asset_context vs get_derivatives_context) and does not mention prerequisites or filtering.

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