get_gex

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

With no annotations, the description carries the full burden. It explains the meaning of positive/negative GEX and what the tool returns (GEX by strike, total GEX, key levels), going beyond a simple mutation description. It doesn't disclose data sources, rate limits, or potential errors, but for a read-oriented analytics tool the provided context is adequate.

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 is well-structured with purpose, explanation, use cases, args, and returns. It front-loads the core purpose and is not verbose. The GEX interpretation section might be considered extra, but it adds value for understanding the output. No wasted words.

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 tool with no annotations and no output schema, the description provides enough to understand what it does, when to use it, and what it returns. It lacks detailed return format or data source specifics, but the essential context for selection and invocation is present.

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 has no parameter descriptions (0% coverage), but the description compensates thoroughly with an Args section for all three parameters, including semantics and defaults (e.g., 'expiration: Specific expiration or None for aggregate' and 'aggregate: Whether to aggregate across all expirations'). This adds meaning beyond the bare schema types.

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 opens with a specific verb+resource: 'Get Gamma Exposure (GEX) levels and flip points.' It then explains what GEX measures and distinguishes it from other options analytics tools by focusing on gamma exposure and dealer positioning. This clearly differentiates it from siblings like get_charm_exposure or get_third_order_greeks.

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?

Explicitly states 'Use this tool when the user asks about:' followed by a list of scenarios (gamma exposure, support/resistance from options, dealer hedging, market maker positioning). This provides clear when-to-use guidance, though it does not name alternative tools directly. The listed use cases are specific and actionable.

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