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

The description goes well beyond the readOnly and destructive annotations. It discloses that data may be up to 5 days stale, that prob_itm can be null when the model is unavailable, and specifies exact error conditions when chain data or the contract is missing. This gives the agent a clear behavioral model of the tool.

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-organized into purpose, process, returns, errors, and args. The first sentence front-loads the core action, and every section earns its place without redundant filler.

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?

The description covers return fields, data freshness, error behavior, and parameter formats. Even though an output schema is said to exist, the description's Returns list and error details give an agent everything needed to invoke the tool and interpret results correctly.

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?

Schema description coverage is 0%, so the description carries the full burden. The Args section fully compensates by documenting every parameter with a type, a concrete example, and format constraints (e.g., 'YYYY-MM-DD', numeric strike, option_type must be 'call' or 'put').

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?

First sentence names a specific verb and resource: 'Get Helium's proprietary ML model-predicted price for a specific option contract.' The process description—looks up the options chain, matches the exact contract, runs it through the model—makes the tool's function unmistakable and clearly distinguishes it from historical-data siblings like get_historical_options_data.

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?

No explicit when-to-use or when-not-to-use guidance is given, and no sibling alternatives are named. The intended use is implied by the purpose statement, but an agent is not explicitly told to prefer this tool over get_historical_options_data or to avoid it when raw market prices are needed.

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