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

No annotations are provided, so the description must carry the behavioral burden. It usefully discloses the return format (OHLCV with implied probability and trend direction) and a per-call cost of $0.003 USDC, but it omits auth/payment requirements, rate limits, and data-range/pagination behavior.

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?

Three short sentences, front-loaded with purpose and return data; the cost note earns its place because it affects invocation. There is no boilerplate or repetition.

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 two-parameter read-only data tool with no output schema, the description supplies the key return-shape and cost context. It could be more complete about history range or pagination, but the essentials for correct selection and invocation are 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?

Schema description coverage is 100%, so both symbol and timeframe are already documented in the schema. The description adds no parameter-specific semantics beyond the general purpose, which is acceptable at the baseline for fully documented inputs.

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?

States a specific verb and resource ('Get historical price/probability data for a Drift BET market') and names the returned data shape. It is clearly historical-market data, but it does not explicitly distinguish itself from sibling drift_market_details or prediction_market_history.

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?

Includes a use case ('charting and analysis') but gives no when-not conditions and does not point to alternatives such as drift_market_details or prediction_market_history. The context is clear enough to infer its role, but routing between siblings is left to the agent.

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